陆地生物圈模型的发展与应用

doi:10.17521/cjpe.2019.0315

摘要/Abstract

摘要：

陆地生物圈与大气圈和水圈之间能量、水和碳氮等元素的交换和循环对整个地球系统产生了深刻的影响。陆地生物圈模型(TBM)是研究陆地生态系统如何响应和反馈全球变化的重要方法和工具。通过对从生态系统到区域和全球陆地生物圈不同空间尺度的植被动态、生物地球物理和生物地球化学循环过程、水循环和水文过程、自然干扰和人类活动等过程时间动态的模拟, 陆地生物圈模型被广泛地应用于评估和归因过去陆地生物圈的时空变化和预测陆地生物圈对未来全球变化的响应和反馈。该文简要回顾了陆地生物圈模型的发展, 总结了模型对陆地生态系统主要过程的刻画和模型在生态系统生态学的应用, 并对未来陆地生物圈模型的发展和应用进行了展望。

关键词: 陆地生物圈模型, 陆地生物圈, 生态系统生态学, 生态系统研究, 全球变化, 碳循环

Abstract:

Exchanges of energy and matter between terrestrial biosphere and atmosphere and hydrosphere create critical feedbacks to Earth’s climates. To quantify how terrestrial ecosystems respond and feedback to global changes, terrestrial biosphere model (TBM) has been developed and applied in global change ecology during the past decades. In TBMs, myriad of biogeophysical, biogeochemical, hydrological cycles and dynamics processes on different spatial and temporal scales are represented. The TBMs have been applied on assessing and attributing past changes in terrestrial biosphere, and on predicting future changes and their feedbacks to climates. Here, we provide an overview of processes included in TBMs and TBMs applications on carbon and hydrological cycles, as well as their application on exploring human impacts on terrestrial ecosystems. Finally, we outline perspectives for future development and application of TBMs.

Key words: terrestrial biosphere model, terrestrial biosphere, ecosystem ecology, ecosystem research, global change, carbon cycle

彭书时, 岳超, 常锦峰. 陆地生物圈模型的发展与应用. 植物生态学报, 2020, 44(4): 436-448. DOI: 10.17521/cjpe.2019.0315

PENG Shu-Shi, YUE Chao, CHANG Jin-Feng. Developments and applications of terrestrial biosphere model. Chinese Journal of Plant Ecology, 2020, 44(4): 436-448. DOI: 10.17521/cjpe.2019.0315

导出引用管理器 EndNote|Ris|BibTeX

链接本文: https://www.plant-ecology.com/CN/10.17521/cjpe.2019.0315

https://www.plant-ecology.com/CN/Y2020/V44/I4/436

图/表 1

参考文献 71

[1]	Bastrikov V, MacBean N, Bacour C, Santaren D, Kuppel S, Peylin P (2018). Land surface model parameter optimisation using in situ flux data: comparison of gradient-based versus random search algorithms (a case study using ORCHIDEE v1.9.5.2). Geoscientific Model Development, 11, 4739-4754.
[2]	Blanke J, Boke-Olén N, Olin S, Chang JF, Sahlin U, Lindeskog M, Lehsten V (2018). Implications of accounting for management intensity on carbon and nitrogen balances of European grasslands. PLOS ONE, 13, e0201058. DOI: 10.1371/journal.pone.0201058. URL PMID
[3]	Bodman RW, Rayner PJ, Karoly DJ (2013). Uncertainty in temperature projections reduced using carbon cycle and climate observations. Nature Climate Change, 3, 725-729.
[4]	Bowring SPK, Lauerwald R, Guenet B, Zhu D, Guimberteau M, Tootchi A, Ducharne A, Ciais P (2019). ORCHIDEE MICT-LEAK (r5459), a global model for the production, transport, and transformation of Dissolved organic carbon from Arctic permafrost regions—Part 1: Rationale, model description, and simulation protocol. Geoscientific Model Development, 12, 3503-3521.
[5]	Bradford MA, Wieder WR, Bonan GB, Fierer N, Raymond PA, Crowther TW (2016). Managing uncertainty in soil carbon feedbacks to climate change. Nature Climate Change, 6, 751-758.
[6]	Brisson N, Mary B, Ripoche D, Jeuffroy MH, Ruget F, Nicoullaud B, Gate P, Devienne-Barret F, Antonioletti R, Durr C, Richard G, Beaudoin N, Recous S, Tayot X, Plenet D, Cellier P, MacHet JM, Meynard JM, Delécolle R (1998). STICS: a generic model for the simulation of crops and their water and nitrogen balances. I. Theory and parameterization applied to wheat and corn. Agronomie, 18, 311-346.
[7]	Carlson KM, Gerber JS, Mueller ND, Herrero M, MacDonald GK, Brauman KA, Havlik P, O’Connell CS, Johnson JA, Saatchi S, West PC (2017). Greenhouse gas emissions intensity of global croplands. Nature Climate Change, 7, 63-68.
[8]	Chang JF, Ciais P, Herrero M, Havlik P, Campioli M, Zhang XZ, Bai YF, Viovy N, Joiner J, Wang XH, Peng SS, Yue C, Piao SL, Wang T, Hauglustaine DA, Soussana JF, Peregon A, Kosykh N, Mironycheva-Tokareva N (2016). Combining livestock production information in a process-based vegetation model to reconstruct the history of grassland management. Biogeosciences, 13, 3757-3776. DOI URL
[9]	Chang JF, Ciais P, Viovy N, Soussana JF, Klumpp K, Sultan B (2017). Future productivity and phenology changes in European grasslands for different warming levels: implications for grassland management and carbon balance. Carbon Balance and Management, 12. DOI: 10.1186/s13021-017-0079-8.
[10]	Chang JF, Ciais P, Viovy N, Vuichard N, Sultan B, Soussana JF (2015). The greenhouse gas balance of European grasslands. Global Change Biology, 21, 3748-3761. URL PMID
[11]	Chang JF, Viovy N, Vuichard N, Ciais P, Wang T, Cozic A, Lardy R, Graux AI, Klumpp K, Martin R, Soussana JF (2013). Incorporating grassland management in ORCHIDEE: model description and evaluation at 11 eddy-covariance sites in Europe. Geoscientific Model Development, 6, 2165-2181. DOI URL
[12]	Dangal SRS, Tian HQ, Lu CQ, Pan SF, Pederson N, Hessl A (2016). Synergistic effects of climate change and grazing on net primary production of Mongolian grasslands. Ecosphere, 7, e01274. DOI: 10.1002/ecs2.1274.
[13]	de Rosnay P, Polcher J (1998). Modelling root water uptake in a complex land surface scheme coupled to a GCM. Hydrology and Earth System Sciences, 2, 239-255.
[14]	de Rosnay P, Polcher J, Bruen M, Laval K (2002). Impact of a physically based soil water flow and soil-plant interaction representation for modeling large-scale land surface processes. Journal of Geophysical Research, 107, 4118. DOI: 10.1029/2001JD000634.
[15]	Ducoudré NI, Laval K, Perrier A (1993). SECHIBA, a new set of parameterizations of the hydrologic exchanges at the land-atmosphere interface within the LMD atmospheric general circulation model. Journal of Climate, 6, 248-273.
[16]	Elliott J, Müller C, Deryng D, Chryssanthacopoulos J, Boote KJ, Büchner M, Foster I, Glotter M, Heinke J, Iizumi T, Izaurralde RC, Mueller ND, Ray DK, Rosenzweig C, Ruane AC, Sheffield J (2015). The Global Gridded Crop Model Intercomparison: data and modeling protocols for Phase 1 (v1.0). Geoscientific Model Development, 8, 261-277.
[17]	Fisher JB, Huntzinger DN, Schwalm CR, Sitch S (2014). Modeling the terrestrial biosphere. Annual Review of Environment and Resources, 39, 91-123.
[18]	Fleischer K, Rammig A, de Kauwe MG, Walker AP, Domingues TF, Fuchslueger L, Garcia S, Goll DS, Grandis A, Jiang MK, Haverd V, Hofhansl F, Holm JA, Kruijt B, Leung F, Medlyn BE, Mercado LM, Norby RJ, Pak B, von Randow C, Quesada CA, Schaap KJ, Valverde-Barrantes OJ, Wang YP, Yang XJ, Zaehle S, Zhu Q, Lapola DM (2019). Amazon forest response to CO₂ fertilization dependent on plant phosphorus acquisition. Nature Geoscience, 12, 736-741.
[19]	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. Journal of Climate, 19, 3337-3353.
[20]	Friedlingstein P, Meinshausen M, Arora VK, Jones CD, Anav A, Liddicoat SK, Knutti R (2014). Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks. Journal of Climate, 27, 511-526.
[21]	Friend AD, Stevens AK, Knox RG, Cannell MGR (1997). A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v3.0). Ecological Modelling, 95, 249-287.
[22]	Goll DS, Brovkin V, Parida BR, Reick CH, Kattge J, Reich PB, van Bodegom PM, Niinemets Ü (2012). Nutrient limitation reduces land carbon uptake in simulations with a model of combined carbon, nitrogen and phosphorus cycling. Biogeosciences, 9, 3547-3569.
[23]	Goll DS, Vuichard N, Maignan F, Jornet-Puig A, Sardans J, Violette A, Peng SS, Sun Y, Kvakic M, Guimberteau M, Guenet B, Zaehle S, Penuelas J, Janssens I, Ciais P (2017). A representation of the phosphorus cycle for ORCHIDEE (revision 4520). Geoscientific Model Development, 10, 3745-3770.
[24]	Graux AI, Gaurut M, Agabriel J, Baumont R, Delagarde R, Delaby L, Soussana JF (2011). Development of the Pasture Simulation Model for assessing livestock production under climate change. Agriculture, Ecosystems & Environment, 144, 69-91.
[25]	Guimberteau M, Ciais P, Ducharne A, Boisier JP, Dutra Aguiar AP, Biemans H, de Deurwaerder H, Galbraith D, Kruijt B, Langerwisch F, Poveda G, Rammig A, Rodriguez DA, Tejada G, Thonicke K, von Randow C, von Randow RCS, Zhang K, Verbeeck H (2017). Impacts of future deforestation and climate change on the hydrology of the Amazon Basin: a multi-model analysis with a new set of land-cover change scenarios. Hydrology and Earth System Sciences, 21, 1455-1475. DOI URL
[26]	Guimberteau M, Zhu D, Maignan F, Huang Y, Yue C, Dantec- Nédélec S, Ottlé C, Jornet-Puig A, Bastos A, Laurent P, Goll D, Bowring S, Chang J, Guenet B, Tifafi M, Peng S, Krinner G, Ducharne A, Wang F, Wang T, Wang X, Wang Y, Yin Z, Lauerwald R, Joetzjer E, Qiu C, Kim H, Ciais P (2018). ORCHIDEE-MICT (v8.4.1), a land surface model for the high latitudes: model description and validation. Geoscientific Model Development, 11, 121-163.
[27]	Huntzinger DN, Michalak AM, Schwalm C, Ciais P, King AW, Fang Y, Schaefer K, Wei Y, Cook RB, Fisher JB, Hayes D, Huang M, Ito A, Jain AK, Lei H, Lu C, Maignan F, Mao J, Parazoo N, Peng S, Poulter B, Ricciuto D, Shi X, Tian H, Wang W, Zeng N, Zhao F (2017). Uncertainty in the response of terrestrial carbon sink to environmental drivers undermines carbon-climate feedback predictions. Scientific Reports, 7, 4765. DOI: 10.1038/s41598-017-03818-2. URL PMID
[28]	Huntzinger DN, Schwalm C, Michalak AM, Schaefer K, King AW, Wei Y, Jacobson A, Liu S, Cook RB, Post WM, Berthier G, Hayes D, Huang M, Ito A, Lei H, Lu C, Mao J, Peng CH, Peng S, Poulter B, Riccuito D, Shi X, Tian H, Wang W, Zeng N, Zhao F, Zhu Q (2013). The north American carbon program multi-scale synthesis and terrestrial model intercomparison project—Part 1: overview and experimental design. Geoscientific Model Development, 6, 2121-2133.
[29]	IPCC (2013). Climate Change 2013: the Physical Science Basis. Cambridge University Press, Cambridge, UK.
[30]	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 Biogeochemical Cycles, 19, GB1015. DOI: 10.1029/2003gb002199.
[31]	Kuppel S, Peylin P, Maignan F, Chevallier F, Kiely G, Montagnani L, Cescatti A (2014). Model-data fusion across ecosystems: from multisite optimizations to global simulations. Geoscientific Model Development, 7, 2581-2597.
[32]	Lawrence DM, Hurtt GC, Arneth A, Brovkin V, Calvin KV, Jones AD, Jones CD, Lawrence PJ, de Noblet-Ducoudré N, Pongratz J, Seneviratne SI, Shevliakova E (2016). The Land Use Model Intercomparison Project (LUMIP) contribution to CMIP6: rationale and experimental design. Geoscientific Model Development, 9, 2973-2998.
[33]	Le Quéré C, Andrew RM, Friedlingstein P, Sitch S, Hauck J, Pongratz J, Pickers PA, Korsbakken JI, Peters GP, Canadell JG, Arneth A, Arora VK, Barbero L, Bastos A, Bopp L, Chevallier F, Chini LP, Ciais P, Doney SC, Gkritzalis T, Goll DS, Harris I, Haverd V, Hoffman FM, Hoppema M, Houghton RA, Hurtt G, Ilyina T, Jain AK, Johannessen T, Jones CD, Kato E, Keeling RF, Goldewijk KK, Landschützer P, Lefèvre N, Lienert S, Liu Z, Lombardozzi D, Metzl N, Munro DR, Nabel JEMS, Nakaoka SI, Neill C, Olsen A, Ono T, Patra P, Peregon A, Peters W, Peylin P, Pfeil B, Pierrot D, Poulter B, Rehder G, Resplandy L, Robertson E, Rocher M, Rödenbeck C, Schuster U, Schwinger J, Séférian R, Skjelvan I, Steinhoff T, Sutton A, Tans PP, Tian HQ, Tilbrook B, Tubiello FN, van der Laan-Luijkx IT, van der Werf GR, Viovy N, Walker AP, Wiltshire AJ, Wright R, Zaehle S, Zheng B (2018). Global carbon budget 2018. Earth System Science Data, 10, 2141-2194. DOI URL
[34]	Lehmann J, Kleber M (2015). The contentious nature of soil organic matter. Nature, 528, 60-68. DOI URL PMID
[35]	Li F, Lawrence DM (2017). Role of fire in the global land water budget during the twentieth century due to changing ecosystems. Journal of Climate, 30, 1893-1908. DOI URL
[36]	McGuire AD, Lawrence DM, Koven C, Clein JS, Burke E, Chen GS, Jafarov E, MacDougall AH, Marchenko S, Nicolsky D, Peng SS, Rinke A, Ciais P, Gouttevin I, Hayes DJ, Ji DY, Krinner G, Moore JC, Romanovsky V, Schädel C, Schaefer K, Schuur EAG, Zhuang QL (2018). Dependence of the evolution of carbon dynamics in the northern permafrost region on the trajectory of climate change. Proceedings of the National Academy of Sciences of the United States of America, 115, 3882-3887. URL PMID
[37]	Medlyn BE, Zaehle S, de Kauwe MG, Walker AP, Dietze MC, Hanson PJ, Hickler T, Jain AK, Luo YQ, Parton W, Prentice IC, Thornton PE, Wang SS, Wang YP, Weng ES, Iversen CM, McCarthy HR, Warren JM, Oren R, Norby RJ (2015). Using ecosystem experiments to improve vegetation models. Nature Climate Change, 5, 528-534. DOI URL
[38]	Moorcroft PR, Hurtt GC, Pacala SW (2001). A method for scaling vegetation dynamics: the ecosystem demography model (ED). Ecological Monographs, 71, 557-586. DOI URL
[39]	Muller A, Schader C, El-Hage Scialabba N, Brüggemann J, Isensee A, Erb KH, Smith P, Klocke P, Leiber F, Stolze M, Niggli U (2017). Strategies for feeding the world more sustainably with organic agriculture. Nature Communications, 8, 1290. DOI: 10.1038/s41467-017-01410-w. URL PMID
[40]	Naudts K, Chen Y, McGrath MJ, Ryder J, Valade A, Otto J, Luyssaert S (2016). Europes forest management did not mitigate climate warming. Science, 351, 597-600. URL PMID
[41]	Norby RJ, Warren JM, Iversen CM, Medlyn BE, McMurtrie RE (2010). CO₂ enhancement of forest productivity constrained by limited nitrogen availability. Proceedings of the National Academy of Sciences of the United States of America, 107, 19368-19373. URL PMID
[42]	Parton WJ, Ojima DS, Cole CV, Schimel DS (1994). A General Model for Soil Organic Matter Dynamics: Sensitivity to Litter Chemistry, Texture and Management. Quantitative Modeling of Soil Forming Processes. Soil Science Society of America, Madison, Wisconsin, USA.
[43]	Piao S, Friedlingstein P, Ciais P, de Noblet-Ducoudré N, Labat D, Zaehle S (2007). Changes in climate and land use have a larger direct impact than rising CO₂ on global river runoff trends. Proceedings of the National Academy of Sciences of the United States of America, 104, 15242-15247. DOI URL PMID
[44]	Pitman AJ, de Noblet-Ducoudré N, Cruz FT, Davin EL, Bonan GB, Brovkin V, Claussen M, Delire C, Ganzeveld L, Gayler V, van den Hurk BJJM, Lawrence PJ, van der Molen MK, Müller C, Reick CH, Seneviratne SI, Strengers BJ, Voldoire A (2009). Uncertainties in climate responses to past land cover change: first results from the LUCID intercomparison study. Geophysical Research Letters, 36, L14814. DOI: 10.1029/2009GL039076. DOI URL
[45]	Prentice IC, Bondeau A, Cramer W, Harrison SP, Hickler T, Lucht W, Sitch S, Smith B, Sykes MT (2007). Dynamic Global Vegetation Modeling: Quantifying Terrestrial Ecosystem Responses to Large-scale Environmental Change. Terrestrial Ecosystems in a Changing World. Springer, Berlin.
[46]	Prentice IC, Cowling SA (2013). Dynamic global vegetation models//Levin SA. Encyclopedia of Biodiversity. 2nd ed. Elsevier, Amsterdam.
[47]	Qiu CJ, Zhu D, Ciais P, Guenet B, Krinner G, Peng SS, Aurela M, Bernhofer C, Brümmer C, Bret-Harte S, Chu HS, Chen JQ, Desai AR, Dušek J, Euskirchen ES, Fortuniak K, Flanagan LB, Friborg T, Grygoruk M, Gogo S, Grünwald T, Hansen BU, Holl D, Humphreys E, Hurkuck M, Kiely G, Klatt J, Kutzbach L, Largeron C, Laggoun-Défarge F, Lund M, Lafleur PM, Li XF, Mammarella I, Merbold L, Nilsson MB, Olejnik J, Ottosson-Löfvenius M, Oechel W, Parmentier FJW, Peichl M, Pirk N, Peltola O, Pawlak W, Rasse D, Rinne J, Shaver G, Schmid HP, Sottocornola M, Steinbrecher R, Sachs T, Urbaniak M, Zona D, Ziemblinska K (2018). ORCHIDEE-PEAT (revision 4596), a model for northern peatland CO₂, water, and energy fluxes on daily to annual scales. Geoscientific Model Development, 11, 497-519. DOI URL
[48]	Rabin SS, Melton JR, Lasslop G, Bachelet D, Forrest M, Hantson S, Kaplan JO, Li F, Mangeon S, Ward DS, Yue C, Arora VK, Hickler T, Kloster S, Knorr W, Nieradzik L, Spessa A, Folberth GA, Sheehan T, Voulgarakis A, Kelley DI, Prentice IC, Sitch S, Harrison S, Arneth A (2017). The Fire Modeling Intercomparison Project (FireMIP), phase 1: experimental and analytical protocols with detailed model descriptions. Geoscientific Model Development, 10, 1175-1197. DOI URL
[49]	Riedo M, Grub A, Rosset M, Fuhrer J (1998). A pasture simulation model for dry matter production, and fluxes of carbon, nitrogen, water and energy. Ecological Modelling, 105, 141-183. DOI URL
[50]	Rolinski S, Müller C, Heinke J, Weindl I, Biewald A, Bodirsky BL, Bondeau A, Boons-Prins ER, Bouwman AF, Leffelaar PA, te Roller JA, Schaphoff S, Thonicke K (2018). Modeling vegetation and carbon dynamics of managed grasslands at the global scale with LPJmL 3.6. Geoscientific Model Development, 11, 429-451. DOI URL
[51]	Rothermel RC (1972). A Mathematical Model for Predicting Fire Spread in Wildland Fuels. USDA Forest Service General Technical Report INT-115. Intermountain Forest and Range Experiment Station, Forest Service, US Dept. of Agriculture, Ogden, Utah.
[52]	Ryder J, Polcher J, Peylin P, Ottlé C, Chen Y, van Gorsel E, Haverd V, McGrath MJ, Naudts K, Otto J, Valade A, Luyssaert S (2016). A multi-layer land surface energy budget model for implicit coupling with global atmospheric simulations. Geoscientific Model Development, 9, 223-245. DOI URL
[53]	Santini M, Caporaso L (2018). Evaluation of freshwater flow from rivers to the sea in CMIP5 simulations: insights from the Congo river basin. Journal of Geophysical Research, 123, 10278-10300.
[54]	Seidl R, Thom D, Kautz M, Martin-Benito D, Peltoniemi M, Vacchiano G, Wild J, Ascoli D, Petr M, Honkaniemi J, Lexer MJ, Trotsiuk V, Mairota P, Svoboda M, Fabrika M, Nagel TA, Reyer CPO (2017). Forest disturbances under climate change. Nature Climate Change, 7, 395-402. URL PMID
[55]	Sellers PJ, Dickinson RE, Randall DA, Betts AK, Hall FG, Berry JA, Collatz GJ, Denning AS, Mooney HA, Nobre CA, Sato N, Field CB, Henderson-Sellers A (1997). Modeling the exchanges of energy, water, and carbon between continents and the atmosphere. Science, 275, 502-509. URL PMID
[56]	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, 653-679. DOI URL
[57]	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. Global Change Biology, 9, 161-185. DOI URL
[58]	Sokol NW, Sanderman J, Bradford MA (2019). Pathways of mineral-associated soil organic matter formation: integrating the role of plant carbon source, chemistry, and point of entry. Global Change Biology, 25, 12-24. URL PMID
[59]	Tang JY, Riley WJ (2017). SUPECA kinetics for scaling redox reactions in networks of mixed substrates and consumers and an example application to aerobic soil respiration. Geoscientific Model Development, 10, 3277-3295. DOI URL
[60]	Terrer C, Vicca S, Stocker BD, Hungate BA, Phillips RP, Reich PB, Finzi AC, Prentice IC (2018). Ecosystem responses to elevated CO₂ governed by plant-soil interactions and the cost of nitrogen acquisition. New Phytologist, 217, 507-522. URL PMID
[61]	Vitousek PM, Porder S, Houlton BZ, Chadwick OA (2010). Terrestrial phosphorus limitation: mechanisms, implications, and nitrogen-phosphorus interactions. Ecological Applications, 20, 5-15. DOI URL PMID
[62]	Watt AS (1947). Pattern and process in the plant community. Journal of Ecology, 35, 1-22. DOI URL
[63]	Wieder WR, Bonan GB, Allison SD (2013). Global soil carbon projections are improved by modelling microbial processes. Nature Climate Change, 3, 909-912. DOI URL
[64]	Wieder WR, Hartman MD, Sulman BN, Wang YP, Koven CD, Bonan GB (2018). Carbon cycle confidence and uncertainty: exploring variation among soil biogeochemical models. Global Change Biology, 24, 1563-1579. URL PMID
[65]	Wu X, Vuichard N, Ciais P, Viovy N, de Noblet-Ducoudré N, Wang X, Magliulo V, Wattenbach M, Vitale L, di Tommasi P, Moors EJ, Jans W, Elbers J, Ceschia E, Tallec T, Bernhofer C, Grünwald T, Moureaux C, Manise T, Ligne A, Cellier P, Loubet B, Larmanou E, Ripoche D (2016). ORCHIDEE-CROP (v0), a new process-based agro-land surface model: model description and evaluation over Europe. Geoscientific Model Development, 9, 857-873. DOI URL
[66]	Yang H, Piao SL, Zeng ZZ, Ciais P, Yin Y, Friedlingstein P, Sitch S, Ahlström A, Guimberteau M, Huntingford C, Levis S, Levy PE, Huang MT, Li Y, Li XR, Lomas MR, Peylin P, Poulter B, Viovy N, Zaehle S, Zeng N, Zhao F, Wang L (2015). Multicriteria evaluation of discharge simulation in dynamic global vegetation models. Journal of Geophysical Research, 120, 7488-7505.
[67]	Yin XY, Struik PC, Romero P, Harbinson J, Evers JB, van der Putten PEL, Vos J (2009). Using combined measurements of gas exchange and chlorophyll fluorescence to estimate parameters of a biochemical C₃ photosynthesis model: a critical appraisal and a new integrated approach applied to leaves in a wheat (Triticum aestivum) canopy. Plant, Cell & Environment, 32, 448-464. URL PMID
[68]	Zaehle S, Jones CD, Houlton B, Lamarque JF, Robertson E (2015). Nitrogen availability reduces CMIP5 projections of twenty-first-century land carbon uptake. Journal of Climate, 28, 2494-2511. DOI URL
[69]	Zaehle S, Medlyn BE, de Kauwe MG, Walker AP, Dietze MC, Hickler T, Luo YQ, Wang YP, El-Masri B, Thornton P, Jain A, Wang SS, Warlind D, Weng ES, Parton W, Iversen CM, Gallet-Budynek A, McCarthy H, Finzi A, Hanson PJ, Prentice IC, Oren R, Norby RJ (2014). Evaluation of 11 terrestrial carbon-nitrogen cycle models against observations from two temperate Free-Air CO₂ Enrichment studies. New Phytologist, 202, 803-822. DOI URL PMID
[70]	Zhu D, Ciais P, Chang JF, Krinner G, Peng SS, Viovy N, Peñuelas J, Zimov S (2018). The large mean body size of mammalian herbivores explains the productivity paradox during the Last Glacial Maximum. Nature Ecology & Evolution, 2, 640-649. DOI URL PMID
[71]	Zhu ZC, Piao SL, Myneni RB, Huang MT, Zeng ZZ, Canadell JG, Ciais P, Sitch S, Friedlingstein P, Arneth A, Cao CX, Cheng L, Kato E, Koven C, Li Y, Lian X, Liu YW, Liu RG, Mao JF, Pan YZ, Peng SS, Peñuelas J, Poulter B, Pugh TAM, Stocker BD, Viovy N, Wang XH, Wang YP, Xiao ZQ, Yang H, Zaehle S, Zeng N (2016). Greening of the earth and its drivers. Nature Climate Change, 6, 791-795. DOI URL