EGU2020-10523, updated on 12 Jun 2020
https://doi.org/10.5194/egusphere-egu2020-10523
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Constraining carbon allocation in a terrestrial ecosystem model using long-term forest biomass time series

Simon Besnard1,2, Sujan Koirala1, Maurizio Santoro3, Shanning Bao1, Oliver Cartus3, Fabian Gans1, Martin Jung1, Tina Trautmann1, and Nuno Carvalhais1,4
Simon Besnard et al.
  • 1Department for Biogeochemical Integration, Max-Planck-Institute for Biogeochemistry, Jena, Germany
  • 2Laboratory of Geo-Information Science and Remote Sensing, Wageningen University & Research, The Netherlands
  • 3GAMMA Remote Sensing Research and Consulting AG, Bern, Switzerland
  • 4CENSE, Departamento de Ciências e Engenharia do Ambiente, Faculdade de Ciências e Tecnologia, Universidade NOVA de Lisboa, Caparica, Portugal

Forests cover about 30% of the terrestrial surface of our planet and store a large part of the terrestrial carbon (C), indicating their fundamental role in terrestrial C dynamics. In recent years, significant advances have been made in understanding terrestrial C cycling across scales, albeit uncertainties remain about fundamental processes, such as photosynthesis, allocation, and mortality, which exert dominant controls on vegetation C dynamics. Allocation plays a critical role in forest ecosystem C cycling by partitioning the products of net photosynthesis into leaves, wood, and below-ground components but is still poorly represented mostly given limitations in process understanding as well as in both suitable and commensurate observations.

Here, we explore different approaches in constraining C allocation alongside processes driving assimilation and out fluxes in a terrestrial ecosystem model based on novel forest biomass datasets. More specifically, we use a series of temporally changing above-ground biomass (AGB) data from local (i.e. in-situ forest inventory data) to global (i.e. long-term C-band satellite retrievals from 1992 to 2018) scales, in a multi-constraint approach. We explore the information contained in a novel AGB time series to diagnose the potential of using changes in vegetation C stocks, jointly with C and water fluxes, to constrain and parameterize different C allocation modeling approaches. Both at FLUXNET site level and global scale, we will: i) present these novel AGB datasets, their strengths and limitations, ii) demonstrate the relevance of constraining C allocation with such temporally changing AGB estimates, and iii) provide a comparison of different C allocation approaches (i.e. fixed versus dynamic allocation, and an hybrid modeling approach) and their implications in representing ecosystem dynamics.

How to cite: Besnard, S., Koirala, S., Santoro, M., Bao, S., Cartus, O., Gans, F., Jung, M., Trautmann, T., and Carvalhais, N.: Constraining carbon allocation in a terrestrial ecosystem model using long-term forest biomass time series, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-10523, https://doi.org/10.5194/egusphere-egu2020-10523, 2020

Display materials

Display file