Publications

Google Scholar | ResearchGate

Submitted, under review, or in revision

Bacour, C., F. Maignan, N. MacBean, A. Porcar-Castell, J. Flexas, C. Frankenberg, P. Peylin, F. Chevallier and N. Vuichard, Improving estimates of Gross Primary Productivity by assimilating solar-induced fluorescence satellite retrievals in a terrestrial biosphere model using a mechanistic SIF model. In revision for JGR-Biogeosciences.

Bacour, C., F. Maignan, P. Peylin, N. MacBean, V. Bastrikov, J. Joiner, P. Köhler, L. Guanter, and C. Frankenberg, Differences between OCO2 and GOME2 SIF products from a model-data fusion perspective. In revision for JGR-Biogeosciences.

Published

2019

[26] Smith, W.K., M. Dannenberg, D. Yan, S. Herrmann, M.L. Barnes, G.A. Barron-Gafford, J.A. Biederman, S. Ferrenberg, A.M. Fox, A.R. Hudson, J.F. Knowles, N. MacBean, D.J.P. Moore, P.L. Nagler, S.C. Reed, W.A. Rutherford, R.L. Scott, X. Wang and J. Yang (2019), Remote sensing of dryland ecosystem structure and function: Progress, challenges and opportunities. Accepted in Remote Sensing of Environment.

[25] Smith, W.K., A. Fox, N. MacBean, D.J.P. Moore and N. Parazoo (2019), Constraining estimates of terrestrial carbon uptake: New opportunities using long-term satellite observations and data assimilation. New Phytologist doi: 10.1111/nph.16055. (Invited Tansley Insight). url pdf

[24] Duncanson, L., J. Armston, M. Disney, V. Avitabile, N. Barbier, K. Calders, S. Carter, J. Chave, M. Herold, T. Crowther, M. Falkowski, J. Kellner, N. Labrière, R. Lucas, N. MacBean, R.E. McRoberts, V. Meyer, E. Næsset, J.E. Nickeson, K.I. Paul, O.L. Phillips, M. Réjou- Méchain, M. Román, S. Roxburgh, S. Saatchi, D. Schepashenko, K. Scipal, P.R. Siqueira, M. Williams, and A. Whitehurst (2019), The Importance of Consistent Global Forest Aboveground Biomass Product Validation. Surveys in Geophysics, 40, 979-999. doi: 10.1007/s10712-019-09538-8. url

[23] Exbrayat, J.-F., A. A. Bloom, N. Carvalhais, R. Fischer, A. Huth, N. MacBean and M. Williams (2019), Understanding the land carbon cycle with space data: current status and prospects. Surveys in Geophysics, 40, 735-755. doi: 10.1007/s10712-019-09506-2. url

2018

[22] Bastrikov, V., N. MacBean, C. Bacour, D. Santaren, S. Kuppel and P. Peylin (2018), Land surface model parameter optimisation using in-situ flux data: comparison of gradient-based versus random search algorithms, Geoscientific Model Development, 11, 4739-4754. pdf

[21] Fox, A.M., T.J. Hoar, J.L. Anderson, A.F. Arellano, W.K. Smith, M.E. Litvak, N. MacBean, D.S. Schimel, and D.J.P. Moore (2018), Evaluation of a Data Assimilation System for Land Surface Models using CLM4.5. Journal of Advances in Modeling Earth Systems, 10, 2471–24942. pdf

[20] Liu, D., Y. Li, T. Wang, P. Peylin, N. MacBean, P. Ciais, G. Jia, M. Ma, Y. Ma, M. Shen,  X. Zhang and S. Piao (2018), Contrasting responses of grassland water and carbon exchanges to climate change between the Tibetan Plateau and Inner Mongolia, Agricultural and Forest Meteorology, 249, 163-175. url

[19] MacBean, N., F. Maignan, C. Bacour, P. Lewis, P. Peylin, L. Guanter, P. Köhler, J. Gomez-Dans and M. Disney (2018), Strong constraint on modeled global carbon uptake using solar-induced chlorophyll fluorescence data, Scientific Reports, 8, 1973, doi: 10.1038/s41598-018-20024-w. pdf

[18] Li, W., N. MacBean, P. Ciais, P. Defourny, C. Lamarche, S. Bontemps, R. A. Houghton and S. Peng (2018), Gross and net land cover changes based on plant functional types derived from the annual ESA CCI land cover maps. Earth Syst. Sci. Data, 10, 219-234. pdf

[17] Smith, W.K., J.A Biederman, R.L. Scott, D.J.P. Moore, M. He, J.S. Kimball, D. Yan, A. Hudson, M.L. Barnes, N. MacBean, A. Fox and M.E. Litvak (2018), Chlorophyll fluorescence better captures seasonal and interannual gross primary productivity dynamics across dryland ecosystems of southwestern North America, Geophys. Res. Lett., 45, 748757url

2017

[16] Hartley, A., N. MacBean, G. Georgievski and S. Bontemps (2017), Uncertainty in plant functional type distributions and its impact on land surface models. Remote Sensing of Environment, 203, 71-89. url

[15] Montané, F., Fox, A. M., Arellano, A. F., MacBean, N., Alexander, M. R., Dye, A., Bishop, D. A., Trouet, V., Babst, F., Hessl, A. E., Pederson, N., Blanken, P. D., Bohrer, G., Gough, C. M., Litvak, M. E., Novick, K. A., Phillips, R. P., Wood, J. D., and Moore, D. J. P. (2017), Evaluating the effect of alternative carbon allocation schemes in a land surface model (CLM4.5) on carbon fluxes, pools and turnover in temperate forests, Geosci. Model Dev. 10, 3499-3517, https://doi.org/10.5194/gmd-10-3499-2017.  pdf

[14] Li, Y., H. Yang, T. Wang, N. MacBean, C. Bacour, P. Ciais, Y. Zhang, G. Zhou and S. Piao (2017), Reducing the uncertainty of parameters controlling seasonal carbon and water fluxes in Chinese forests, and its implication for simulated climate sensitivities, Global Biogeochemical Cycles, 31, doi:10.1002/2017GB005714.

[13] Walker, A. P., T. Quaife, P. M. van Bodegom, M. G. De Kauwe, T. F. Keenan, J. Joiner, M. R. Lomas, N. MacBean, C. Xu, X. Yang and F. I. Woodward (2017), The impact of alternative trait-scaling hypotheses for the maximum photosynthetic carboxylation rate (Vcmax) on global gross primary production, New Phytologist, 215, 1370–1386, doi:10.1111/nph.14623. url

[12] Thum, T., N. MacBean, P. Peylin, C. Bacour, D. Santaren, B. Longdoz, D. Loustau and P. Ciais (2017) The potential benefit of using forest biomass data in addition to carbon and water flux measurements to constrain ecosystem model parameters: case studies at two temperate forest sites, Agricultural and Forest Meteorology, 234, 48-65. url

2016

[11] MacBean, N., P. Peylin, F. Chevallier, M. Scholze, M., and G. Schürmann (2016) Consistent assimilation of multiple data streams in a carbon cycle data assimilation system, Geoscientific Model Development, 9, 3569-3588, doi:10.5194/gmd-9-3569-2016. url pdf

[10] Peylin, P., C. Bacour, N. MacBean, S. Leonard, P.J. Rayner, S. Kuppel, E.N. Koffi, A. Kane, F. Maignan, F. Chevallier, P. Ciais and P. Prunet (2016), A new step-wise Carbon Cycle Data Assimilation System using multiple data streams to constrain the simulated land surface carbon cycle, Geoscientific Model Development, 9, 3321-3346, doi:10.5194/gmd-9-3321-2016. url pdf

[9] Li, W., P. Ciais, N. MacBeanS. Peng, P. Defourny and S. Bontemps (2016), Major forest changes and land cover transitions based on plant functional types derived from the ESA CCI Land Cover product. International Journal of Applied Earth Observation and Geoinformation, 47, 30-39. url 

2015

[8] MacBean, N., F. Maignan, P. Peylin, C. Bacour, P. Ciais and F.-M. Bréon (2015), Using satellite data to improve the leaf phenology of a global terrestrial biosphere model, Biogeosciences, 12, 7185-7208. url pdf

[7] Bacour, C., P. Peylin, N. MacBean, P. J. Rayer, F. Delage, F. Chevallier,  M. Weiss, J. Demarty, D. Santaren,  F. Baret, D. Berveiller, E. Dufrêne and P. Prunet (2015), Joint assimilation of eddy-covariance flux measurements and satellite observations within a process-oriented biosphere model, Journal of Geophysical Research Biogeosciences, 120, 1839–1857, doi: 10.1002/2015JG002966. url pdf

[6] Poulter, B., N. MacBean, A. Hartley, I. Khlystova, O. Arino, R. Betts,
 S. Bontemps, M. Boettcher, C. Brockmann, P. Defourny, S. Hagemann, M. Herold, G. Kirches, C. Lamarche, D. Lederer, C. Ottlé, M. Peters, and P. Peylin (2015), Plant functional type classification for Earth System Models: results from the European Space Agency’s Land Cover Climate Change Initiative, Geoscientific Model Development, 8, 2315-2328, doi:10.5194/gmd-8-2315-2015. url pdf

[5] Naudts, K., J. Ryder, M. J. McGrath, J. Otto, Y. Chen, A. Valade, V. Bellasen, G. Berhongaray, G. Bönisch, M. Campioli, J. Ghattas, T. De Groote, V. Haverd, J. Kattge, N. MacBean, F. Maignan, P. Merilä, J. Penuelas, P. Peylin, B. Pinty, H. Pretzsch, E. D. Schulze, D. Solyga, N. Vuichard, Y. Yan, and S. Luyssaert (2015) A vertically discretised canopy description for ORCHIDEE (SVN r2290) and the modifications to the energy, water and carbon fluxes, Geoscientific Model Development, 8, 2035-2065. url pdf

[4] Wang, X., S. Piao, X. Xu, P. Ciais, N. MacBean, R.B. Myneni and L. Li (2015) Has the advancing onset of spring vegetation green-up slowed down or changed abruptly over the past three decades? Global Ecology and Biogeography, 24, 621-631, doi: 10.1111/geb12289. url pdf

2014

[3] MacBean, N. and P. Peylin (2014), Biogeochemistry: Agriculture and the Global Carbon Cycle, Nature (News and Views), 515, 351-352, doi: 10.1038/515351a. url pdf

[2] Traore, A., P. Ciais, N. Vuichard, N.MacBean, C. Dardel, B. Poulter, S.    Piao, J.B. Fisher, N. Viovy, M. Jung and R. Myneni (2014) 1982-2010 Trends of Light use Efficiency and Inherent Water use Efficiency in African vegetation: Sensitivity to Climate and Atmospheric CO2 Concentrations, Remote Sensing, 6, 8923-8944, doi: 10.3390/rs6098923. url pdf

2010

[1] Walker, R.T., M. Talebian, S. Saiffori, R.A. Sloan, A. Rasheedi, N. MacBean and A. Ghassemi (2010) Active faulting, earthquakes, and restraining bend development near Kerman city in southeastern Iran, Journal of Structural Geology, 32(8), 1046-1060. url pdf

Conference proceedings

Kato, T., F. Maignan, N. MacBean, P. Peylin, N. Vuichard, Y. Goulas, F. Daumard, I. Moya, A. Porcar-Castell and C. Nicol (2014) Relationship of the model-simulated productivity with the in-situ fluorescence measurements at two flux sites, 5th International Workshop on Remote Sensing of Fluorescence. Paris, France.

MacBean, N., M. Disney, J. Gomez-Dans, P. Lewis and P. Ineson (2010) Using satellite measurements of surface soil moisture to improve estimates of CO2 and CH4 from peatlands, European Space Agency Living Planet Symposium. Bergen, Norway.