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Showing content from https://doi.org/10.5194/gmd-12-4309-2019 below:

The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 1: Model description

Ahlström, A., Schurgers, G., Arneth, A., and Smith, B.: Robustness and uncertainty in terrestrial ecosystem carbon response to CMIP5 climate change projections, Environ. Res. Lett., 7, 044008, https://doi.org/10.1088/1748-9326/7/4/044008, 2012. a

Albani, M., Medvigy, D., Hurtt, G. C., and Moorcroft, P. R.: The contributions of land-use change, CO2 fertilization, and climate variability to the eastern US carbon sink, Glob. Change Biol., 12, 2370–2390, https://doi.org/10.1111/j.1365-2486.2006.01254.x, 2006. a, b, c, d, e, f

Amthor, J. S.: The role of maintenance respiration in plant growth, Plant Cell Environ., 7, 561–569, https://doi.org/10.1111/1365-3040.ep11591833, 1984. a

Antonarakis, A. S., Saatchi, S. S., Chazdon, R. L., and Moorcroft, P. R.: Using Lidar and Radar measurements to constrain predictions of forest ecosystem structure and function, Ecol. Appl., 21, 1120–1137, https://doi.org/10.1890/10-0274.1, 2011. a, b

Antonarakis, A. S., Munger, J. W., and Moorcroft, P. R.: Imaging spectroscopy- and lidar-derived estimates of canopy composition and structure to improve predictions of forest carbon fluxes and ecosystem dynamics, Geophys. Res. Lett., 41, 2535–2542, https://doi.org/10.1002/2013GL058373, 2014. a

Arias, M. E., Lee, E., Farinosi, F., Pereira, F. F., and Moorcroft, P. R.: Decoupling the effects of deforestation and climate variability in the Tapajós river basin in the Brazilian Amazon, Hydrol. Process., 32, 1648–1663, https://doi.org/10.1002/hyp.11517, 2018. a

Avissar, R. and Mahrer, Y.: Mapping frost-sensitive areas with a three-dimensional local-scale numerical model. Part I. Physical and numerical aspects, J. Appl. Meteor., 27, 400–413, https://doi.org/10.1175/1520-0450(1988)027<0400:MFSAWA>2.0.CO;2, 1988. a

Baker, I., Denning, A. S., Hanan, N., Prihodko, L., Uliasz, M., Vidale, P.-L., Davis, K., and Bakwin, P.: Simulated and observed fluxes of sensible and latent heat and CO2 at the WLEF-TV tower using SiB2.5, Glob. Change Biol., 9, 1262–1277, https://doi.org/10.1046/j.1365-2486.2003.00671.x, 2003. a

Bazzaz, F. A.: The physiological ecology of plant succession, Annu. Rev. Ecol. Syst., 10, 351–371, https://doi.org/10.1146/annurev.es.10.110179.002031, 1979. a

Best, M. J., Pryor, M., Clark, D. B., Rooney, G. G., Essery, R. L. H., Ménard, C. B., Edwards, J. M., Hendry, M. A., Porson, A., Gedney, N., Mercado, L. M., Sitch, S., Blyth, E., Boucher, O., Cox, P. M., Grimmond, C. S. B., and Harding, R. J.: The Joint UK Land Environment Simulator (JULES), model description – Part 1: Energy and water fluxes, Geosci. Model Dev., 4, 677–699, https://doi.org/10.5194/gmd-4-677-2011, 2011. a, b

Betts, A. K. and Silva Dias, M. A. F.: Progress in understanding land-surface-atmosphere coupling from LBA research, J. Adv. Model. Earth Syst., 2, 6, https://doi.org/10.3894/JAMES.2010.2.6, 2010. a

Beven, K. and Freer, J.: A dynamic TOPMODEL, Hydrol. Process., 15, 1993–2011, https://doi.org/10.1002/hyp.252, 2001. a

Blyth, E., Clark, D. B., Ellis, R., Huntingford, C., Los, S., Pryor, M., Best, M., and Sitch, S.: A comprehensive set of benchmark tests for a land surface model of simultaneous fluxes of water and carbon at both the global and seasonal scale, Geosci. Model Dev., 4, 255–269, https://doi.org/10.5194/gmd-4-255-2011, 2011. a

Bogan, S. A., Antonarakis, A. S., and Moorcroft, P. R.: Imaging spectrometry-derived estimates of regional ecosystem composition for the Sierra Nevada, California, Remote Sens. Environ., 228, 14–30, https://doi.org/10.1016/j.rse.2019.03.031, 2019. a

Bolker, B. M., Pacala, S. W., and Parton, W. J.: Linear analysis of soil decomposition: insights from the CENTURY model, Ecol. Appl., 8, 425–439, https://doi.org/10.1890/1051-0761(1998)008[0425:LAOSDI]2.0.CO;2, 1998. a, b, c, d

Bonan, G. B.: Land-atmosphere CO2 exchange simulated by a land surface process model coupled to an atmospheric general circulation model, J. Geophys. Res.-Atmos., 100, 2817–2831, https://doi.org/10.1029/94JD02961, 1995. a

Bonan, G. B.: Ecological climatology, Cambridge Univ. Press, Cambridge, UK, 2nd Edn., 2008. a, b

Both, S., Riutta, T., Paine, C. E. T., Elias, D. M. O., Cruz, R. S., Jain, A., Johnson, D., Kritzler, U. H., Kuntz, M., Majalap-Lee, N., Mielke, N., Montoya Pillco, M. X., Ostle, N. J., Arn Teh, Y., Malhi, Y., and Burslem, D. F. R. P.: Logging and soil nutrients independently explain plant trait expression in tropical forests, New Phytol., 221, 1853–1865, https://doi.org/10.1111/nph.15444, 2019. a

Brooks, R. H. and Corey, A. T.: Hydraulic properties of porous media, Hydrology Papers 3, Colorado State University, Fort Collins, USA, 1964. a

Bruelheide, H., Dengler, J., Purschke, O., Lenoir, J., Jiménez-Alfaro, B., Hennekens, S. M., Botta-Dukát, Z., Chytrý, M., Field, R., Jansen, F., Kattge, J., Pillar, V. D., Schrodt, F., Mahecha, M. D., Peet, R. K., Sandel, B., van Bodegom, P., Altman, J., Alvarez-Dávila, E., Arfin Khan, M. A. S., Attorre, F., Aubin, I., Baraloto, C., Barroso, J. G., Bauters, M., Bergmeier, E., Biurrun, I., Bjorkman, A. D., Blonder, B., Čarni, A., Cayuela, L., Černý, T., Cornelissen, J. H. C., Craven, D., Dainese, M., Derroire, G., De Sanctis, M., DÍaz, S., Doležal, J., Farfan-Rios, W., Feldpausch, T. R., Fenton, N. J., Garnier, E., Guerin, G. R., Gutiérrez, A. G., Haider, S., Hattab, T., Henry, G., Hérault, B., Higuchi, P., Hölzel, N., Homeier, J., Jentsch, A., Jürgens, N., Ka̧cki, Z., Karger, D. N., Kessler, M., Kleyer, M., Knollová, I., Korolyuk, A. Y., Kühn, I., Laughlin, D. C., Lens, F., Loos, J., Louault, F., Lyubenova, M. I., Malhi, Y., Marcenò, C., Mencuccini, M., Müller, J. V., Munzinger, J., Myers-Smith, I. H., Neill, D. A., Niinemets, Ü., Orwin, K. H., Ozinga, W. A., Penuelas, J., Pérez-Haase, A., Petřík, P., Phillips, O. L., Pärtel, M., Reich, P. B., Römermann, C., Rodrigues, A. V., Sabatini, F. M., Sardans, J., Schmidt, M., Seidler, G., Silva Espejo, J. E., Silveira, M., Smyth, A., Sporbert, M., Svenning, J.-C., Tang, Z., Thomas, R., Tsiripidis, I., Vassilev, K., Violle, C., Virtanen, R., Weiher, E., Welk, E., Wesche, K., Winter, M., Wirth, C., and Jandt, U.: Global trait–environment relationships of plant communities, Nat. Ecol. Evol., 2, 1906–1917, https://doi.org/10.1038/s41559-018-0699-8, 2018. a

Bugmann, H.: A Review of Forest Gap Models, Clim. Change, 51, 259–305, https://doi.org/10.1023/A:1012525626267, 2001. a

Cardinale, B. J., Wright, J. P., Cadotte, M. W., Carroll, I. T., Hector, A., Srivastava, D. S., Loreau, M., and Weis, J. J.: Impacts of plant diversity on biomass production increase through time because of species complementarity, P. Natl. Acad. Sci. USA, 104, 18123–18128, https://doi.org/10.1073/pnas.0709069104, 2007. a

Castanho, A. D. A., Galbraith, D., Zhang, K., Coe, M. T., Costa, M. H., and Moorcroft, P.: Changing Amazon biomass and the role of atmospheric CO2 concentration, climate and land use, Global Biogeochem. Cy., 30, 18–39, https://doi.org/10.1002/2015GB005135, 2016. a

Cavanaugh, K. C., Gosnell, J. S., Davis, S. L., Ahumada, J., Boundja, P., Clark, D. B., Mugerwa, B., Jansen, P. A., O'Brien, T. G., Rovero, F., Sheil, D., Vasquez, R., and Andelman, S.: Carbon storage in tropical forests correlates with taxonomic diversity and functional dominance on a global scale, Global Ecol. Biogeogr., 23, 563–573, https://doi.org/10.1111/geb.12143, 2014. a

Chen, J. and Black, T.: Foliage area and architecture of plant canopies from sunfleck size distributions, Agr. Forest Meteorol., 60, 249–266, https://doi.org/10.1016/0168-1923(92)90040-B, 1992. a

Clark, D. B., Mercado, L. M., Sitch, S., Jones, C. D., Gedney, N., Best, M. J., Pryor, M., Rooney, G. G., Essery, R. L. H., Blyth, E., Boucher, O., Harding, R. J., Huntingford, C., and Cox, P. M.: The Joint UK Land Environment Simulator (JULES), model description – Part 2: Carbon fluxes and vegetation dynamics, Geosci. Model Dev., 4, 701–722, https://doi.org/10.5194/gmd-4-701-2011, 2011. a

Collatz, G., Ribas-Carbo, M., and Berry, J.: Coupled photosynthesis-stomatal conductance model for leaves of C4 plants, Aust. J. Plant Physiol., 19, 519–538, https://doi.org/10.1071/PP9920519, 1992. a, b, c

Collatz, G. J., Ball, J., Grivet, C., and Berry, J. A.: Physiological and environmental regulation of stomatal conductance, photosynthesis and transpiration: a model that includes a laminar boundary layer, Agr. Forest Meteorol., 54, 107–136, https://doi.org/10.1016/0168-1923(91)90002-8, 1991. a, b

Cowan, I. and Troughton, J.: The relative role of stomata in transpiration and assimilation, Planta, 97, 325–336, https://doi.org/10.1007/BF00390212, 1971. a

Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P., Kobayashi, S., Andrae, U., Balmaseda, M. A., Balsamo, G., Bauer, P., Bechtold, P., Beljaars, A. C. M., van de Berg, L., Bidlot, J., Bormann, N., Delsol, C., Dragani, R., Fuentes, M., Geer, A. J., Haimberger, L., Healy, S. B., Hersbach, H., Hólm, E. V., Isaksen, L., Kållberg, P., Köhler, M., Matricardi, M., McNally, A. P., Monge-Sanz, B. M., Morcrette, J.-J., Park, B.-K., Peubey, C., de Rosnay, P., Tavolato, C., Thépaut, J.-N., and Vitart, F.: The ERA-Interim reanalysis: configuration and performance of the data assimilation system, Q. J. Roy. Meteorol. Soc., 137, 553–597, https://doi.org/10.1002/qj.828, 2011. a

di Porcia e Brugnera, M., Meunier, F., Longo, M., Moorthy, S., De Deurwaerder, H., Schnitzer, S. A., Bonal, D., Faybishenko, B., and Verbeeck, H.: Modelling the impact of liana infestation on the demography and carbon cycle of tropical forests, Global Change Biol., 25, 3767–3780, https://doi.org/10.1111/gcb.14769, 2019. a

Dickinson, R., Henderson-Sellers, A., Kennedy, P., and Wilson, M.: Biosphere-atmosphere transfer scheme (BATS) for the NCAR community climate model, Technical Note NCAR/TN-275+STR, NCAR, Boulder, CO, https://doi.org/10.5065/D6668B58, 1986. a

Dietze, M. C., Serbin, S. P., Davidson, C., Desai, A. R., Feng, X., Kelly, R., Kooper, R., LeBauer, D., Mantooth, J., McHenry, K., and Wang, D.: A quantitative assessment of a terrestrial biosphere model's data needs across North American biomes, J. Geophys. Res.-Biogeosci., 119, 286–300, https://doi.org/10.1002/2013JG002392, 2014. a

Dufour, L. and van Mieghem, J.: Thermodynamique de l'atmosphère, Institut Royal Météorologique de Belgique, Gembloux, Belgium, 2 edn., in French, 1975. a

Evans, M. R.: Modelling ecological systems in a changing world, Philos. Trans. R. Soc. B-Biol. Sci., 367, 181–190, https://doi.org/10.1098/rstb.2011.0172, 2012. a, b

Farquhar, G., von Caemmerer, S., and Berry, J.: A biochemical model of photosynthetic CO2 assimilation in leaves of C3 species, Planta, 149, 78–90, https://doi.org/10.1007/BF00386231, 1980. a, b

Feldpausch, T. R., Jirka, S., Passos, C. A. M., Jasper, F., and Riha, S. J.: When big trees fall: Damage and carbon export by reduced impact logging in southern Amazonia, Forest Ecol. Manag., 219, 199–215, https://doi.org/10.1016/j.foreco.2005.09.003, 2005. a

Feng, X., Uriarte, M., González, G., Reed, S., Thompson, J., Zimmerman, J. K., and Murphy, L.: Improving predictions of tropical forest response to climate change through integration of field studies and ecosystem modeling, Global Change Biol., 24, e213–e232, https://doi.org/10.1111/gcb.13863, 2018. a

Fischer, R., Bohn, F., de Paula, M. D., Dislich, C., Groeneveld, J., Gutiérrez, A. G., Kazmierczak, M., Knapp, N., Lehmann, S., Paulick, S., Pütz, S., Rödig, E., Taubert, F., Köhler, P., and Huth, A.: Lessons learned from applying a forest gap model to understand ecosystem and carbon dynamics of complex tropical forests, Ecol. Model., 326, 124–133, https://doi.org/10.1016/j.ecolmodel.2015.11.018, 2016. a, b

Fisher, J. B., Huntzinger, D. N., Schwalm, C. R., and Sitch, S.: Modeling the terrestrial biosphere, Ann. Rev. Environ. Res., 39, 91–123, https://doi.org/10.1146/annurev-environ-012913-093456, 2014. a

Fisher, R., McDowell, N., Purves, D., Moorcroft, P., Sitch, S., Cox, P., Huntingford, C., Meir, P., and Ian Woodward, F.: Assessing uncertainties in a second-generation dynamic vegetation model caused by ecological scale limitations, New Phytol., 187, 666–681, https://doi.org/10.1111/j.1469-8137.2010.03340.x, 2010. a

Fisher, R. A., Muszala, S., Vertenstein, M., Lawrence, P., Xu, C., McDowell, N. G., Knox, R. G., Koven, C., Holm, J., Rogers, B. M., Lawrence, D., and Bonan, G.: Taking off the training wheels: the properties of a dynamic vegetation model without climate envelopes, Geosci. Model Dev., 8, 3593–3619, https://doi.org/10.5194/gmd-8-3593-2015, 2015. a, b

Fisher, R. A., Koven, C. D., Anderegg, W. R. L., Christoffersen, B. O., Dietze, M. C., Farrior, C., Holm, J. A., Hurtt, G., Knox, R. G., Lawrence, P. J., Lichststein, J. W., Longo, M., Matheny, A. M., Medvigy, D., Muller-Landau, H. C., Powell, T. L., Serbin, S. P., Sato, H., Shuman, J., Smith, B., Trugman, A. T., Viskari, T., Verbeeck, H., Weng, E., Xu, C., Xu, X., Zhang, T., and Moorcroft, P.: Vegetation demographics in Earth system models: a review of progress and priorities, Global Change Biol., 24, 35–54, https://doi.org/10.1111/gcb.13910, 2018. a, b, c, d

Foken, T.: 50 years of the Monin–Obukhov similarity theory, Bound.-Lay. Meteorol., 119, 431–447, https://doi.org/10.1007/s10546-006-9048-6, 2006. a, b

Foley, J. A., Prentice, I. C., Ramankutty, N., Levis, S., Pollard, D., Sitch, S., and Haxeltine, A.: An integrated biosphere model of land surface processes, terrestrial carbon balance, and vegetation dynamics, Global Biogeochem. Cy., 10, 603–628, https://doi.org/10.1029/96GB02692, 1996. a, b, c, d

Fortunel, C., Fine, P. V. A., and Baraloto, C.: Leaf, stem and root tissue strategies across 758 Neotropical tree species, Funct. Ecol., 26, 1153–1161, https://doi.org/10.1111/j.1365-2435.2012.02020.x, 2012. a

Freitas, S. R., Panetta, J., Longo, K. M., Rodrigues, L. F., Moreira, D. S., Rosário, N. E., Silva Dias, P. L., Silva Dias, M. A. F., Souza, E. P., Freitas, E. D., Longo, M., Frassoni, A., Fazenda, A. L., Santos e Silva, C. M., Pavani, C. A. B., Eiras, D., França, D. A., Massaru, D., Silva, F. B., Santos, F. C., Pereira, G., Camponogara, G., Ferrada, G. A., Campos Velho, H. F., Menezes, I., Freire, J. L., Alonso, M. F., Gácita, M. S., Zarzur, M., Fonseca, R. M., Lima, R. S., Siqueira, R. A., Braz, R., Tomita, S., Oliveira, V., and Martins, L. D.: The Brazilian developments on the Regional Atmospheric Modeling System (BRAMS 5.2): an integrated environmental model tuned for tropical areas, Geosci. Model Dev., 10, 189–222, https://doi.org/10.5194/gmd-10-189-2017, 2017. a

Friedlingstein, P., Meinshausen, M., Arora, V. K., Jones, C. D., Anav, A., Liddicoat, S. K., and Knutti, R.: Uncertainties in CMIP5 climate projections due to carbon cycle feedbacks, J. Climate, 27, 511–526, https://doi.org/10.1175/JCLI-D-12-00579.1, 2014. a

Friend, A. D., Stevens, A. K., Knox, R. G., and Cannell, M. G. R.: A process-based, terrestrial biosphere model of ecosystem dynamics (Hybrid v3.0), Ecol. Model., 95, 249–287, https://doi.org/10.1016/S0304-3800(96)00034-8, 1997. a, b

García-Palacios, P., Gross, N., Gaitán, J., and Maestre, F. T.: Climate mediates the biodiversity–ecosystem stability relationship globally, P. Natl. Acad. Sci. USA, 115, 8400–8405, https://doi.org/10.1073/pnas.1800425115, 2018. a

Gelaro, R., McCarty, W., Suárez, M. J., Todling, R., Molod, A., Takacs, L., Randles, C. A., Darmenov, A., Bosilovich, M. G., Reichle, R., Wargan, K., Coy, L., Cullather, R., Draper, C., Akella, S., Buchard, V., Conaty, A., da Silva, A. M., Gu, W., Kim, G.-K., Koster, R., Lucchesi, R., Merkova, D., Nielsen, J. E., Partyka, G., Pawson, S., Putman, W., Rienecker, M., Schubert, S. D., Sienkiewicz, M., and Zhao, B.: The Modern-Era Retrospective Analysis for Research and Applications, version 2 (MERRA-2), J. Climate, 30, 5419–5454, https://doi.org/10.1175/JCLI-D-16-0758.1, 2017. a

Global Soil Data Task: Global Soil Data Products CD-ROM Contents (IGBP-DIS), https://doi.org/10.3334/ORNLDAAC/565, Oak Ridge National Laboratory Distributed Active Archive Center, Oak Ridge, Tennessee, USA, 2000. a

Good, P., Jones, C., Lowe, J., Betts, R., Booth, B., and Huntingford, C.: Quantifying Environmental Drivers of Future Tropical Forest Extent, J. Climate, 24, 1337–1349, https://doi.org/10.1175/2010JCLI3865.1, 2011. a, b

Haddad, N. M., Brudvig, L. A., Clobert, J., Davies, K. F., Gonzalez, A., Holt, R. D., Lovejoy, T. E., Sexton, J. O., Austin, M. P., Collins, C. D., Cook, W. M., Damschen, E. I., Ewers, R. M., Foster, B. L., Jenkins, C. N., King, A. J., Laurance, W. F., Levey, D. J., Margules, C. R., Melbourne, B. A., Nicholls, A. O., Orrock, J. L., Song, D.-X., and Townshend, J. R.: Habitat fragmentation and its lasting impact on Earth's ecosystems, Science Advances, 1, e1500052, https://doi.org/10.1126/sciadv.1500052, 2015. a

Haverd, V., Cuntz, M., Leuning, R., and Keith, H.: Air and biomass heat storage fluxes in a forest canopy: Calculation within a soil vegetation atmosphere transfer model, Agr. Forest Meteorol., 147, 125–139, https://doi.org/10.1016/j.agrformet.2007.07.006, 2007. a

Haxeltine, A. and Prentice, I. C.: BIOME3: An equilibrium terrestrial biosphere model based on ecophysiological constraints, resource availability, and competition among plant functional types, Global Biogeochem. Cy., 10, 693–709, https://doi.org/10.1029/96GB02344, 1996. a

Hengl, T., de Jesus, J. M., Heuvelink, G. B. M., Ruiperez Gonzalez, M., Kilibarda, M., Blagotić, A., Shangguan, W., Wright, M. N., Geng, X., Bauer Marschallinger, B., Guevara, M. A., Vargas, R., MacMillan, R. A., Batjes, N. H., Leenaars, J. G. B., Ribeiro, E., Wheeler, I., Mantel, S., and Kempen, B.: SoilGrids250m: Global gridded soil information based on machine learning, PLoS One, 12, 1–40, https://doi.org/10.1371/journal.pone.0169748, 2017. a

Huang, M., Xu, Y., Longo, M., Keller, M., Knox, R., Koven, C., and Fisher, R.: Assessing impacts of selective logging on water, energy, and carbon budgets and ecosystem dynamics in Amazon forests using the Functionally Assembled Terrestrial Ecosystem Simulator, Biogeosciences Discuss., https://doi.org/10.5194/bg-2019-129, in review, 2019. a

Huang, Y., Chen, Y., Castro-Izaguirre, N., Baruffol, M., Brezzi, M., Lang, A., Li, Y., Härdtle, W., von Oheimb, G., Yang, X., Liu, X., Pei, K., Both, S., Yang, B., Eichenberg, D., Assmann, T., Bauhus, J., Behrens, T., Buscot, F., Chen, X.-Y., Chesters, D., Ding, B.-Y., Durka, W., Erfmeier, A., Fang, J., Fischer, M., Guo, L.-D., Guo, D., Gutknecht, J. L. M., He, J.-S., He, C.-L., Hector, A., Hönig, L., Hu, R.-Y., Klein, A.-M., Kühn, P., Liang, Y., Li, S., Michalski, S., Scherer-Lorenzen, M., Schmidt, K., Scholten, T., Schuldt, A., Shi, X., Tan, M.-Z., Tang, Z., Trogisch, S., Wang, Z., Welk, E., Wirth, C., Wubet, T., Xiang, W., Yu, M., Yu, X.-D., Zhang, J., Zhang, S., Zhang, N., Zhou, H.-Z., Zhu, C.-D., Zhu, L., Bruelheide, H., Ma, K., Niklaus, P. A., and Schmid, B.: Impacts of species richness on productivity in a large-scale subtropical forest experiment, Science, 362, 80–83, https://doi.org/10.1126/science.aat6405, 2018. a

Hughes, J. K., Valdes, P. J., and Betts, R. A.: Dynamical properties of the TRIFFID dynamic global vegetation model, Technical Note HCTN, No. 56, U.K. Met Office Hadley Centre, Exeter, UK, 2004. a

Hurtt, G. C., Moorcroft, P. R., Pacala, S. W., and Levin, S. A.: Terrestrial models and global change: challenges for the future, Global Change Biol., 4, 581–590, https://doi.org/10.1046/j.1365-2486.1998.t01-1-00203.x, 1998. a

Hurtt, G. C., Pacala, S. W., Moorcroft, P. R., Caspersen, J., Shevliakova, E., Houghton, R. A., and Moore, B.: Projecting the future of the U.S. carbon sink, P. Natl. Acad. Sci. USA, 99, 1389–1394, https://doi.org/10.1073/pnas.012249999, 2002. a, b, c

Hurtt, G. C., Frolking, S., Fearon, M. G., Moore, B., Shevliakova, E., Malyshev, S., Pacala, S. W., and Houghton, R. A.: The underpinnings of land-use history: three centuries of global gridded land-use transitions, wood-harvest activity, and resulting secondary lands., Global Change Biol., 12, 1208–1229, https://doi.org/10.1111/j.1365-2486.2006.01150.x, 2006. a

Hutchings, M. J.: The Structure of Plant Populations, chap. 11, 325–358, Wiley-Blackwell, Oxford, U.K., 2nd Edn., https://doi.org/10.1002/9781444313642.ch11, 1997. a

IPCC: Climate change 2014: impacts, adaptation, and vulnerability. Part A: global and sectoral aspects, Cambridge Univ. Press, Cambridge, UK and New York, NY, USA, 2014. a

Ise, T., Dunn, A. L., Wofsy, S. C., and Moorcroft, P. R.: High sensitivity of peat decomposition to climate change through water-table feedback, Nat. Geosci., 1, 763–766, https://doi.org/10.1038/ngeo331, 2008. a

Jin, J., Gao, X., Sorooshian, S., Yang, Z.-L., Bales, R., Dickinson, R. E., Sun, S.-F., and Wu, G.-X.: One-dimensional snow water and energy balance model for vegetated surfaces, Hydrol. Process., 13, 2467–2482, https://doi.org/10.1002/(SICI)1099-1085(199910)13:14/15<2467::AID-HYP861>3.0.CO;2-J, 1999. a

Jucker, T. and Coomes, D. A.: Comment on “Plant Species Richness and Ecosystem Multifunctionality in Global Drylands”, Science, 337, 155, https://doi.org/10.1126/science.1220473, 2012. a

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.: Seasonal carbon dynamics and water fluxes in an Amazon rainforest, Global Change Biol., 18, 1322–1334, https://doi.org/10.1111/j.1365-2486.2011.02629.x, 2012. a

Knox, R. G., Longo, M., Swann, A. L. S., Zhang, K., Levine, N. M., Moorcroft, P. R., and Bras, R. L.: Hydrometeorological effects of historical land-conversion in an ecosystem-atmosphere model of Northern South America, Hydrol. Earth Syst. Sci., 19, 241–273, https://doi.org/10.5194/hess-19-241-2015, 2015. a, b, c, d

Lambers, H., Chapin III, F. S., and Pons, T. L.: Plant physiological ecology, Springer, New York, USA, 2nd Edn., https://doi.org/10.1007/978-0-387-78341-3, 2008.  a, b, c, d

LeBauer, D. S., Wang, D., Richter, K. T., Davidson, C. C., and Dietze, M. C.: Facilitating feedbacks between field measurements and ecosystem models, Ecol. Monogr., 83, 133–154, https://doi.org/10.1890/12-0137.1, 2013. a

Le Page, Y., Morton, D., Bond-Lamberty, B., Pereira, J. M. C., and Hurtt, G.: HESFIRE: a global fire model to explore the role of anthropogenic and weather drivers, Biogeosciences, 12, 887–903, https://doi.org/10.5194/bg-12-887-2015, 2015. a

Le Quéré, C., Andrew, R. M., Friedlingstein, P., Sitch, S., Hauck, J., Pongratz, J., Pickers, P. A., Korsbakken, J. I., Peters, G. P., Canadell, J. G., Arneth, A., Arora, V. K., Barbero, L., Bastos, A., Bopp, L., Chevallier, F., Chini, L. P., Ciais, P., Doney, S. C., Gkritzalis, T., Goll, D. S., Harris, I., Haverd, V., Hoffman, F. M., Hoppema, M., Houghton, R. A., Hurtt, G., Ilyina, T., Jain, A. K., Johannessen, T., Jones, C. D., Kato, E., Keeling, R. F., Goldewijk, K. K., Landschützer, P., Lefèvre, N., Lienert, S., Liu, Z., Lombardozzi, D., Metzl, N., Munro, D. R., Nabel, J. E. M. S., Nakaoka, S.-I., 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, P. P., Tian, H., Tilbrook, B., Tubiello, F. N., van der Laan Luijkx, I. T., van der Werf, G. R., Viovy, N., Walker, A. P., Wiltshire, A. J., Wright, R., Zaehle, S., and Zheng, B.: Global carbon budget 2018, Earth Syst. Sci. Data, 10, 2141–2194, https://doi.org/10.5194/essd-10-2141-2018, 2018. a, b

Lee, T. J. and Pielke, R. A.: Estimating the Soil Surface Specific Humidity, J. Appl. Meteor., 31, 480–484, https://doi.org/10.1175/1520-0450(1992)031<0480:ETSSSH>2.0.CO;2, 1992. a

Leuning, R.: A critical appraisal of a combined stomatal-photosynthesis model for C3 plants, Plant Cell Environ., 18, 339–355, https://doi.org/10.1111/j.1365-3040.1995.tb00370.x, 1995. a, b, c

Levine, N. M., Zhang, K., Longo, M., Baccini, A., Phillips, O. L., Lewis, S. L., Alvarez, E., de Andrade, A. C. S., Brienen, R., Erwin, T., Feldpausch, T. R., Mendoza, A. L. M., Vargas, P. N., Prieto, A., Espejo, J. E. S., Malhi, Y., and Moorcroft, P. R.: Ecosystem heterogeneity determines the resilience of the Amazon to climate change, P. Natl. Acad. Sci. USA, 113, 793–797, https://doi.org/10.1073/pnas.1511344112, 2016. a, b, c, d

Levis, S.: Modeling vegetation and land use in models of the Earth System, WIREs Clim. Change, 1, 840–856, https://doi.org/10.1002/wcc.83, 2010. a

Levis, S., Bonan, G., Vertenstein, M., and Oleson, K.: The Community Land Model's Dynamic Global Vegetation Model (CLM-DGVM): Technical description and user's guide, Technical Note NCAR/TN-459+IA, NCAR, Boulder, CO, https://doi.org/10.5065/D6P26W36, 2004. a

Lewis, S. L., Edwards, D. P., and Galbraith, D.: Increasing human dominance of tropical forests, Science, 349, 827–832, https://doi.org/10.1126/science.aaa9932, 2015. a, b

Liang, J., Crowther, T. W., Picard, N., Wiser, S., Zhou, M., Alberti, G., Schulze, E.-D., McGuire, A. D., Bozzato, F., Pretzsch, H., de Miguel, S., Paquette, A., Hérault, B., Scherer-Lorenzen, M., Barrett, C. B., Glick, H. B., Hengeveld, G. M., Nabuurs, G.-J., Pfautsch, S., Viana, H., Vibrans, A. C., Ammer, C., Schall, P., Verbyla, D., Tchebakova, N., Fischer, M., Watson, J. V., Chen, H. Y. H., Lei, X., Schelhaas, M.-J., Lu, H., Gianelle, D., Parfenova, E. I., Salas, C., Lee, E., Lee, B., Kim, H. S., Bruelheide, H., Coomes, D. A., Piotto, D., Sunderland, T., Schmid, B., Gourlet-Fleury, S., Sonké, B., Tavani, R., Zhu, J., Brandl, S., Vayreda, J., Kitahara, F., Searle, E. B., Neldner, V. J., Ngugi, M. R., Baraloto, C., Frizzera, L., Bałazy, R., Oleksyn, J., Zawiła-Niedźwiecki, T., Bouriaud, O., Bussotti, F., Finér, L., Jaroszewicz, B., Jucker, T., Valladares, F., Jagodzinski, A. M., Peri, P. L., Gonmadje, C., Marthy, W., O'Brien, T., Martin, E. H., Marshall, A. R., Rovero, F., Bitariho, R., Niklaus, P. A., Alvarez-Loayza, P., Chamuya, N., Valencia, R., Mortier, F., Wortel, V., Engone-Obiang, N. L., Ferreira, L. V., Odeke, D. E., Vasquez, R. M., Lewis, S. L., and Reich, P. B.: Positive biodiversity-productivity relationship predominant in global forests, Science, 354, aaf8957, https://doi.org/10.1126/science.aaf8957, 2016. a

Lindeskog, M., Arneth, A., Bondeau, A., Waha, K., Seaquist, J., Olin, S., and Smith, B.: Implications of accounting for land use in simulations of ecosystem carbon cycling in Africa, Earth Syst. Dynam., 4, 385–407, https://doi.org/10.5194/esd-4-385-2013, 2013. a

Liou, K. N.: An introduction to atmospheric radiation, vol. 84 of International Geophysics Series, Academic Press, San Diego, CA, USA, 2nd Edn., 2002. a, b

Lloyd, J., Patiño, S., Paiva, R. Q., Nardoto, G. B., Quesada, C. A., Santos, A. J. B., Baker, T. R., Brand, W. A., Hilke, I., Gielmann, H., Raessler, M., Luizão, F. J., Martinelli, L. A., and Mercado, L. M.: Optimisation of photosynthetic carbon gain and within-canopy gradients of associated foliar traits for Amazon forest trees, Biogeosciences, 7, 1833–1859, https://doi.org/10.5194/bg-7-1833-2010, 2010. a

Lombardozzi, D. L., Smith, N. G., Cheng, S. J., Dukes, J. S., Sharkey, T. D., Rogers, A., Fisher, R., and Bonan, G. B.: Triose phosphate limitation in photosynthesis models reduces leaf photosynthesis and global terrestrial carbon storage, Environ. Res. Lett., 13, 074025, https://doi.org/10.1088/1748-9326/aacf68, 2018. a, b

Longo, M. and Keller, M.: Not the same old(-growth) forest, New Phytol., 221, 1672–1675, https://doi.org/10.1111/nph.15636, 2019. a

Longo, M., Knox, R. G., Levine, N. M., Alves, L. F., Bonal, D., Camargo, P. B., Fitzjarrald, D. R., Hayek, M. N., Restrepo-Coupe, N., Saleska, S. R., da Silva, R., Stark, S. C., Tapajós, R. P., Wiedemann, K. T., Zhang, K., Wofsy, S. C., and Moorcroft, P. R.: Ecosystem heterogeneity and diversity mitigate Amazon forest resilience to frequent extreme droughts, New Phytol., 219, 914–931, https://doi.org/10.1111/nph.15185, 2018. a, b

Longo, M., Knox, R. G., Levine, N. M., Swann, A. L. S., Medvigy, D. M., Dietze, M. C., Kim, Y., Zhang, K., Bonal, D., Burban, B., Camargo, P. B., Hayek, M. N., Saleska, S. R., da Silva, R., Bras, R. L., Wofsy, S. C., and Moorcroft, P. R.: The biophysics, ecology, and biogeochemistry of functionally diverse, vertically and horizontally heterogeneous ecosystems: the Ecosystem Demography model, version 2.2 – Part 2: Model evaluation for tropical South America, Geosci. Model Dev., 12, 4347–4374, https://doi.org/10.5194/gmd-12-4347-2019, 2019a. a, b, c

Longo, M., Knox, R. G., Medvigy, D. M., Levine, N. M., Dietze, M. C., Swann, A. L. S., Zhang, K., Rollinson, C. R., di Porcia e Brugnera, M., Scott, D., Serbin, S. P., Kooper, R., Pourmokhtarian, A., Shiklomanov, A., Viskari, T., and Moorcroft, P.: Ecosystem Demography Model, version 2.2 (ED-2.2) (Version rev-86), https://doi.org/10.5281/zenodo.3365659, Zenodo, 2019b. a

Loreau, M. and Hector, A.: Partitioning selection and complementarity in biodiversity experiments, Nature, 412, 72–76, https://doi.org/10.1038/35083573, 2001. a

Manabe, S., Smagorinsky, J., and Strickler, R. F.: Simulated climatology of a general circulation model with a hydrologic cycle, Mon. Weather Rev., 93, 769–798, https://doi.org/10.1175/1520-0493(1965)093<0769:SCOAGC>2.3.CO;2, 1965. a

Mangeon, S., Voulgarakis, A., Gilham, R., Harper, A., Sitch, S., and Folberth, G.: INFERNO: a fire and emissions scheme for the UK Met Office's Unified Model, Geosci. Model Dev., 9, 2685–2700, https://doi.org/10.5194/gmd-9-2685-2016, 2016. a

Maréchaux, I. and Chave, J.: An individual-based forest model to jointly simulate carbon and tree diversity in Amazonia: description and applications, Ecol. Monogr., 87, 632–664, https://doi.org/10.1002/ecm.1271, 2017. a

Medvigy, D. and Moorcroft, P. R.: Predicting ecosystem dynamics at regional scales: an evaluation of a terrestrial biosphere model for the forests of northeastern North America, Philos. Trans. R. Soc. B-Biol. Sci., 367, 222–235, https://doi.org/10.1098/rstb.2011.0253, 2012. a

Medvigy, D., Wang, G., Zhu, Q., Riley, W. J., Trierweiler, A. M., Waring, B. G., Xu, X., and Powers, J. S.: Observed variation in soil properties can drive large variation in modeled forest functioning and composition during tropical forest secondary succession, New Phytol., 223, 1820–1833, https://doi.org/10.1111/nph.15848, 2019. a

Medvigy, D. M.: The state of the regional carbon cycle: results from a constrained coupled ecosystem-atmosphere model, Ph.D. dissertation, Harvard University, Cambridge, MA, 2006. a, b

Medvigy, D. M., Wofsy, S. C., Munger, J. W., Hollinger, D. Y., and Moorcroft, P. R.: Mechanistic scaling of ecosystem function and dynamics in space and time: Ecosystem Demography model version 2, J. Geophys. Res.-Biogeosci., 114, G01002, https://doi.org/10.1029/2008JG000812, 2009. a, b, c, d, e, f, g

Monin, A. S. and Obukhov, A. M.: Osnovnye zakonomernosti turbulentnogo pere- meshivanija v prizemnom sloe atmosfery (Basic laws of turbulent mixing in the atmosphere near the ground), Trudy Geofiz. Inst. AN SSSR, 24, 163–187, 1954 (in Russian). a

Monteith, J. L. and Unsworth, M. H.: Principles of environmental physics, Academic Press, London, 3rd Edn., 418 pp., 2008. a

Moorcroft, P. R.: Recent advances in ecosystem-atmosphere interactions: an ecological perspective, Proc. R. Soc. Lond. B-Biol. Sci., 270, 1215–1227, https://doi.org/10.1098/rspb.2002.2251, 2003. a

Moorcroft, P. R.: How close are we to a predictive science of the biosphere?, Trends Ecol. Evol., 21, 400–407, https://doi.org/10.1016/j.tree.2006.04.009, 2006. a, b, c

Moorcroft, P. R., Hurtt, G. C., and Pacala, S. W.: A method for scaling vegetation dynamics: The Ecosystem Demography model (ED), Ecol. Monogr., 71, 557–586, https://doi.org/10.1890/0012-9615(2001)071[0557:AMFSVD]2.0.CO;2, 2001. a, b, c, d, e, f, g, h, i, j, k, l

Naeem, S. and Li, S.: Biodiversity enhances ecosystem reliability, Nature, 390, 507–509, https://doi.org/10.1038/37348, 1997. a

Neilson, R. P.: A Model for Predicting Continental-Scale Vegetation Distribution and Water Balance, Ecol. Appl., 5, 362–385, https://doi.org/10.2307/1942028, 1995. a

Noilhan, J. and Planton, S.: A Simple Parameterization of Land Surface Processes for Meteorological Models, Mon. Weather Rev., 117, 536–549, https://doi.org/10.1175/1520-0493(1989)117<0536:ASPOLS>2.0.CO;2, 1989. a

Norby, R. J., Gu, L., Haworth, I. C., Jensen, A. M., Turner, B. L., Walker, A. P., Warren, J. M., Weston, D. J., Xu, C., and Winter, K.: Informing models through empirical relationships between foliar phosphorus, nitrogen and photosynthesis across diverse woody species in tropical forests of Panama, New Phytol., 215, 1425–1437, https://doi.org/10.1111/nph.14319, 2017. a

Oleson, K. W., Lawrence, D. M., Bonan, G. B., Drewniak, B., Huang, M., Koven, C. D., Levis, S., Li, F., Riley, W. J., Subin, Z. M., Swenson, S. C., Thornton, P. E., Bozbiyik, A., Fisher, R., Heald, C. L., Kluzek, E., Lamarque, J.-F., Lawrence, P. J., Leung, L. R., Lipscomb, W., Muszala, S., Ricciuto, D. M., Sacks, W., Sun, Y., Tang, J., and Yang, Z.-L.: Technical description of version 4.5 of the Community Land Model (CLM), Technical Report NCAR/TN-503+STR, NCAR, Boulder, CO, https://doi.org/10.5065/D6RR1W7M, 420pp., 2013. a, b, c, d

Pandit, K., Dashti, H., Glenn, N. F., Flores, A. N., Maguire, K. C., Shinneman, D. J., Flerchinger, G. N., and Fellows, A. W.: Optimizing shrub parameters to estimate gross primary production of the sagebrush ecosystem using the Ecosystem Demography (EDv2.2) model, Geosci. Model Dev. Discuss., https://doi.org/10.5194/gmd-2018-264, in review, 2018. a

Pereira, F. F., Farinosi, F., Arias, M. E., Lee, E., Briscoe, J., and Moorcroft, P. R.: Technical note: A hydrological routing scheme for the Ecosystem Demography model (ED2+R) tested in the Tapajós River basin in the Brazilian Amazon, Hydrol. Earth Syst. Sci., 21, 4629–4648, https://doi.org/10.5194/hess-21-4629-2017, 2017. a

Pereira Jr., R., Zweede, J., Asner, G. P., and Keller, M.: Forest canopy damage and recovery in reduced-impact and conventional selective logging in eastern Para, Brazil, Forest Ecol. Manag., 168, 77–89, https://doi.org/10.1016/S0378-1127(01)00732-0, 2002. a

Philip, J. R.: Evaporation, and moisture and heat fields in the soil, J. Meteor., 14, 354–366, https://doi.org/10.1175/1520-0469(1957)014<0354:EAMAHF>2.0.CO;2, 1957. a

Phillips, O. L., van der Heijden, G., Lewis, S. L., López-González, G., Aragão, L. E. O. C., Lloyd, J., Malhi, Y., Monteagudo, A., Almeida, S., Alvarez Dávila, E., Amaral, I., Andelman, S., Andrade, A., Arroyo, L., Aymard, G., Baker, T. R., Blanc, L., Bonal, D., Alves de Oliveira, A. C., Chao, K.-J., Dávila Cardozo, N., da Costa, L., Feldpausch, T. R., Fisher, J. B., Fyllas, N. M., Freitas, M. A., Galbraith, D., Gloor, E., Higuchi, N., Honorio, E., Jiménez, E., Keeling, H., Killeen, T. J., Lovett, J. C., Meir, P., Mendoza, C., Morel, A., Núñez Vargas, P., Patiño, S., Peh, K. S.-H., Peña Cruz, A., Prieto, A., Quesada, C. A., Ramírez, F., Ramírez, H., Rudas, A., Salamão, R., Schwarz, M., Silva, J., Silveira, M., Slik, J. W. F., Sonké, B., Thomas, A. S., Stropp, J., Taplin, J. R. D., Vásquez, R., and Vilanova, E.: Drought-mortality relationships for tropical forests, New Phytol., 187, 631–646, https://doi.org/10.1111/j.1469-8137.2010.03359.x, 2010. a

Piao, S., Sitch, S., Ciais, P., Friedlingstein, P., Peylin, P., Wang, X., Ahlström, A., Anav, A., Canadell, J. G., Cong, N., Huntingford, C., Jung, M., Levis, S., Levy, P. E., Li, J., Lin, X., Lomas, M. R., Lu, M., Luo, Y., Ma, Y., Myneni, R. B., Poulter, B., Sun, Z., Wang, T., Viovy, N., Zaehle, S., and Zeng, N.: Evaluation of terrestrial carbon cycle models for their response to climate variability and to CO2 trends, Global Change Biol., 19, 2117–2132, https://doi.org/10.1111/gcb.12187, 2013. a

Poorter, L., van der Sande, M. T., Thompson, J., Arets, E. J. M. M., Alarcón, A., Álvarez-Sánchez, J., Ascarrunz, N., Balvanera, P., Barajas-Guzmán, G., Boit, A., Bongers, F., Carvalho, F. A., Casanoves, F., Cornejo-Tenorio, G., Costa, F. R. C., de Castilho, C. V., Duivenvoorden, J. F., Dutrieux, L. P., Enquist, B. J., Fernández-Méndez, F., Finegan, B., Gormley, L. H. L., Healey, J. R., Hoosbeek, M. R., Ibarra-Manríquez, G., Junqueira, A. B., Levis, C., Licona, J. C., Lisboa, L. S., Magnusson, W. E., Martínez-Ramos, M., Martínez-Yrizar, A., Martorano, L. G., Maskell, L. C., Mazzei, L., Meave, J. A., Mora, F., Muñoz, R., Nytch, C., Pansonato, M. P., Parr, T. W., Paz, H., Pérez-García, E. A., Rentería, L. Y., Rodríguez-Velázquez, J., Rozendaal, D. M. A., Ruschel, A. R., Sakschewski, B., Salgado-Negret, B., Schietti, J., Simões, M., Sinclair, F. L., Souza, P. F., Souza, F. C., Stropp, J., ter Steege, H., Swenson, N. G., Thonicke, K., Toledo, M., Uriarte, M., van der Hout, P., Walker, P., Zamora, N., and Peña-Claros, M.: Diversity enhances carbon storage in tropical forests, Global Ecol. Biogeogr., 24, 1314–1328, https://doi.org/10.1111/geb.12364, 2015. a

Powell, T. L., Galbraith, D. R., Christoffersen, B. O., Harper, A., Imbuzeiro, H. M. A., Rowland, L., Almeida, S., Brando, P. M., da Costa, A. C. L., Costa, M. H., Levine, N. M., Malhi, Y., Saleska, S. R., Sotta, E., Williams, M., Meir, P., and Moorcroft, P. R.: Confronting model predictions of carbon fluxes with measurements of Amazon forests subjected to experimental drought, New Phytol., 200, 350–365, https://doi.org/10.1111/nph.12390, 2013. a

Prentice, I. C., Webb, R. S., Ter-Mikhaelian, M. T., Solomon, A. M., Smith, T. M., Pitovranov, S. E., Nikolov, N. T., Minin, A. A., Leemans, R., Lavorel, S., Korzukhin, M. D., Hrabovszky, J. P., Helmisaari, H. O., Harrison, S. P., Emanuel, W. R., and Bonan, G. B.: Developing a global vegetation dynamics model: Results of an IIASA summer workshop, Research Report RR-89-7, International Institute for Applied Systems Analysis, Laxenburg, Austria, available at: http://pure.iiasa.ac.at/3223 (last access: 25 September 2019), 1989. a

Prentice, I. C., Cramer, W., Harrison, S. P., Leemans, R., Monserud, R. A., and Solomon, A. M.: A Global Biome Model Based on Plant Physiology and Dominance, Soil Properties and Climate, J. Biogeogr., 19, 117–134, https://doi.org/10.2307/2845499, 1992. a

Purves, D. and Pacala, S.: Predictive Models of Forest Dynamics, Science, 320, 1452–1453, https://doi.org/10.1126/science.1155359, 2008. a, b

Purves, D. W., Lichstein, J. W., Strigul, N., and Pacala, S. W.: Predicting and understanding forest dynamics using a simple tractable model, P. Natl. Acad. Sci. USA, 105, 17018–17022, https://doi.org/10.1073/pnas.0807754105, 2008. a

Raczka, B., Dietze, M. C., Serbin, S. P., and Davis, K. J.: What limits predictive certainty of long-term carbon uptake?, J. Geophys. Res.-Biogeosci., 123, 3570–3588, https://doi.org/10.1029/2018JG004504, 2018. a

Reich, P. B., Walters, M. B., and Ellsworth, D. S.: From tropics to tundra: Global convergence in plant functioning, P. Natl. Acad. Sci. USA, 94, 13730–13734, https://doi.org/10.1073/pnas.94.25.13730, 1997. a

Rogers, A., Medlyn, B. E., Dukes, J. S., Bonan, G., von Caemmerer, S., Dietze, M. C., Kattge, J., Leakey, A. D. B., Mercado, L. M., Niinemets, U., Prentice, I. C., Serbin, S. P., Sitch, S., Way, D. A., and Zaehle, S.: A roadmap for improving the representation of photosynthesis in Earth system models, New Phytol., 213, 22–42, https://doi.org/10.1111/nph.14283, 2017. a

Santanello Jr, J. A., Dirmeyer, P. A., Ferguson, C. R., Findell, K. L., Tawfik, A. B., Berg, A., Ek, M., Gentine, P., Guillod, B. P., van Heerwaarden, C., Roundy, J., and Wulfmeyer, V.: Land–atmosphere interactions: the LoCo perspective, B. Am. Meteorol. Soc., 99, 1253–1272, https://doi.org/10.1175/BAMS-D-17-0001.1, 2018. a

Sato, H., Itoh, A., and Kohyama, T.: SEIB–DGVM: A new Dynamic Global Vegetation Model using a spatially explicit individual-based approach, Ecol. Model., 200, 279–307, https://doi.org/10.1016/j.ecolmodel.2006.09.006, 2007. a, b

Sellers, P. J.: Canopy reflectance, photosynthesis and transpiration, Int. J. Remote Sens., 6, 1335–1372, https://doi.org/10.1080/01431168508948283, 1985. a, b

Sellers, P. J., Mintz, Y., Sud, Y. C., and Dalcher, A.: A Simple Biosphere model (SIB) for use within general circulation models, J. Atmos. Sci., 43, 505–531, https://doi.org/10.1175/1520-0469(1986)043<0505:ASBMFU>2.0.CO;2, 1986. a

Sellers, P. J., Randall, D. A., Collatz, G. J., Berry, J. A., Field, C. B., Dazlich, D. A., Zhang, C., Collelo, G. D., and Bounoua, L.: A revised land surface parameterization (SiB2) for atmospheric GCMs. Part I: model formulation, J. Climate, 9, 676–705, https://doi.org/10.1175/1520-0442(1996)009<0676:ARLSPF>2.0.CO;2, 1996. a, b

Sellers, P. J., Dickinson, R. E., Randall, D. A., Betts, A. K., Hall, F. G., Berry, J. A., Collatz, G. J., Denning, A. S., Mooney, H. A., Nobre, C. A., Sato, N., Field, C. B., and Henderson-Sellers, A.: Modeling the exchanges of energy, water, and carbon between continents and the atmosphere, Science, 275, 502–509, https://doi.org/10.1126/science.275.5299.502, 1997. a, b, c

Sheffield, J., Goteti, G., and Wood, E. F.: Development of a 50-year high-resolution global dataset of meteorological forcings for land surface modeling, J. Climate, 19, 3088–3111, https://doi.org/10.1175/JCLI3790.1, 2006. a, b

Sitch, S., Smith, B., Prentice, I. C., Arneth, A., Bondeau, A., Cramer, W., Kaplan, J. O., Levis, S., Lucht, W., Sykes, M. T., Thonicke, K., and Venevsky, S.: Evaluation of ecosystem dynamics, plant geography and terrestrial carbon cycling in the LPJ dynamic global vegetation model, Global Change Biol., 9, 161–185, https://doi.org/10.1046/j.1365-2486.2003.00569.x, 2003. a, b

Sitch, S., Huntingford, C., Gedney, N., Levy, P. E., Lomas, M., Piao, S. L., Betts, R., Ciais, P., Cox, P., Friedlingstein, P., Jones, C. D., Prentice, I. C., and Woodward, F. I.: 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, 2015–2039, https://doi.org/10.1111/j.1365-2486.2008.01626.x, 2008. a

Smith, B., Prentice, I. C., and Sykes, M. T.: Representation of vegetation dynamics in the modelling of terrestrial ecosystems: comparing two contrasting approaches within European climate space, Global Ecol. Biogeogr., 10, 621–637, https://doi.org/10.1046/j.1466-822X.2001.t01-1-00256.x, 2001. a

Soares-Filho, B. S., Nepstad, D. C., Curran, L. M., Cerqueira, G. C., Garcia, R. A., Ramos, C. A., Voll, E., McDonald, A., Lefebvre, P., and Schlesinger, P.: Modelling conservation in the Amazon basin, Nature, 440, 520–523, https://doi.org/10.1038/nature04389, 2006. a

Somerville, R., Stone, P., Halem, M., Hansen, J., Hogan, J., Druyan, L., Russell, G., Lacis, A., Quirk, W., and Tenenbaum, J.: The GISS model of the global atmosphere, J. Atmos. Sci., 31, 84–117, https://doi.org/10.1175/1520-0469(1974)031<0084:TGMOTG>2.0.CO;2, 1974. a

Swann, A. L. S., Longo, M., Knox, R. G., Lee, E., and Moorcroft, P. R.: Future deforestation in the Amazon and consequences for South American climate, Agr. Forest Meteorol., 214–215, 12–24, https://doi.org/10.1016/j.agrformet.2015.07.006, 2015. a, b, c, d

The ED-2 model development team: Ecosystem Demography model (ED-2) code repository, available at: https://github.com/EDmodel/ED2 (last access: 25 September 2019), 2014. 

The HDF Group: Hierarchical data format, version 5, available at: http://www.hdfgroup.org/HDF5/ (last access: 25 September 2019), 2016. a

Thonicke, K., Spessa, A., Prentice, I. C., Harrison, S. P., Dong, L., and Carmona-Moreno, C.: The influence of vegetation, fire spread and fire behaviour on biomass burning and trace gas emissions: results from a process-based model, Biogeosciences, 7, 1991–2011, https://doi.org/10.5194/bg-7-1991-2010, 2010. a

Tilman, D. and Downing, John, A.: Biodiversity and stability in grasslands, Nature, 367, 363–365, https://doi.org/10.1038/367363a0, 1994. a

Tilman, D., Isbell, F., and Cowles, J. M.: Biodiversity and ecosystem functioning, Ann. Rev. Ecol. Evol. Syst., 45, 471–493, https://doi.org/10.1146/annurev-ecolsys-120213-091917, 2014. a

Trugman, A. T., Medvigy, D., Hoffmann, W. A., and Pellegrini, A. F. A.: Sensitivity of woody carbon stocks to bark investment strategy in Neotropical savannas and forests, Biogeosciences, 15, 233–243, https://doi.org/10.5194/bg-15-233-2018, 2018. a, b

Vidale, P. L. and Stöckli, R.: Prognostic canopy air space solutions for land surface exchanges, Theor. Appl. Climatol., 80, 245–257, https://doi.org/10.1007/s00704-004-0103-2, 2005. a

von Caemmerer, S.: Biochemical models of leaf photosynthesis, no. 2 in Techniques in Plant Sciences, CSIRO Publishing, Collingwood, VIC, Australia, https://doi.org/10.1006/anbo.2000.1296, 2000. a, b

Walko, R. L., Band, L. E., Baron, J., Kittel, T. G. F., Lammers, R., Lee, T. J., Ojima, D., Pielke, R. A., Taylor, C., Tague, C., Tremback, C. J., and Vidale, P. L.: Coupled atmosphere–biophysics–hydrology models for environmental modeling, J. Appl. Meteor., 39, 931–944, https://doi.org/10.1175/1520-0450(2000)039<0931:CABHMF>2.0.CO;2, 2000. a, b, c, d, e, f, g

Wang, J.-W., Denning, A. S., Lu, L., Baker, I. T., Corbin, K. D., and Davis, K. J.: Observations and simulations of synoptic, regional, and local variations in atmospheric CO2, J. Geophys. Res.-Atmos., 112, D04108, https://doi.org/10.1029/2006JD007410, 2007. a

Weedon, G. P., Balsamo, G., Bellouin, N., Gomes, S., Best, M. J., and Viterbo, P.: The WFDEI meteorological forcing data set: WATCH forcing data methodology applied to ERA-Interim reanalysis data, Water Resour. Res., 50, 7505–7514, https://doi.org/10.1002/2014WR015638, 2014. a

Weng, E. S., Malyshev, S., Lichstein, J. W., Farrior, C. E., Dybzinski, R., Zhang, T., Shevliakova, E., and Pacala, S. W.: Scaling from individual trees to forests in an Earth system modeling framework using a mathematically tractable model of height-structured competition, Biogeosciences, 12, 2655–2694, https://doi.org/10.5194/bg-12-2655-2015, 2015. a, b

Wohlfahrt, G., Bianchi, K., and Cernusca, A.: Leaf and stem maximum water storage capacity of herbaceous plants in a mountain meadow, J. Hydrol., 319, 383–390, https://doi.org/10.1016/j.jhydrol.2005.06.036, 2006. a

Wright, I. J., Reich, P. B., Westoby, M., Ackerly, D. D., Baruch, Z., Bongers, F., Cavender-Bares, J., Chapin, T., Cornelissen, J. H. C., Diemer, M., Flexas, J., Garnier, E., Groom, P. K., Gulias, J., Hikosaka, K., Lamont, B. B., Lee, T., Lee, W., Lusk, C., Midgley, J. J., Navas, M.-L., Niinemets, U., Oleksyn, J., Osada, N., Poorter, H., Poot, P., Prior, L., Pyankov, V. I., Roumet, C., Thomas, S. C., Tjoelker, M. G., Veneklaas, E. J., and Villar, R.: The worldwide leaf economics spectrum, Nature, 428, 821–827, https://doi.org/10.1038/nature02403, 2004. a

Xu, X., Medvigy, D., Powers, J. S., Becknell, J. M., and Guan, K.: Diversity in plant hydraulic traits explains seasonal and inter-annual variations of vegetation dynamics in seasonally dry tropical forests, New Phytol., 212, 80–95, https://doi.org/10.1111/nph.14009, 2016. a, b, c

Xu, X., Medvigy, D., Wright, S. J., Kitajima, K., Wu, J., Albert, L. P., Martins, G. A., Saleska, S. R., and Pacala, S. W.: Variations of leaf longevity in tropical moist forests predicted by a trait-driven carbon optimality model, Ecol. Lett., 20, 1097–1106, https://doi.org/10.1111/ele.12804, 2017. a

Yang, Y., Saatchi, S. S., Xu, L., Yu, Y., Choi, S., Phillips, N., Kennedy, R., Keller, M., Knyazikhin, Y., and Myneni, R. B.: Post-drought decline of the Amazon carbon sink, Nat. Comm., 9, 3172, https://doi.org/10.1038/s41467-018-05668-6, 2018. a

Zhang, K., Castanho, A. D. D. A., Galbraith, D. R., Moghim, S., Levine, N., Bras, R. L., Coe, M., Costa, M. H., Malhi, Y., Longo, M., Knox, R. G., McKnight, S., Wang, J., and Moorcroft, P. R.: The fate of Amazonian ecosystems over the coming century arising from changes in climate, atmospheric CO2 and land-use, Global Change Biol., 21, 2569–2587, https://doi.org/10.1111/gcb.12903, 2015. a, b


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