4.7 Article

The Role of Respiration in Estimation of Net Carbon Cycle: Coupling Soil Carbon Dynamics and Canopy Turnover in a Novel Version of 3D-CMCC Forest Ecosystem Model

期刊

FORESTS
卷 8, 期 6, 页码 -

出版社

MDPI
DOI: 10.3390/f8060220

关键词

forest ecosystem; Fluxnet; soil respiration; net ecosystem exchange; phenology

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资金

  1. Gordon and Betty Moore Foundation's Data-Driven Discovery Initiative [GBMF4563]
  2. Italian Ministry of Education, University and Research
  3. Italian Ministry of Environment and Protection of Land and Sea under the project GEMINA [232/2011]
  4. University of Tuscia
  5. European Union's Horizon research and innovation program [641816]
  6. ALForLab project - National Operational Program for Research and Competitiveness (PON R&C), through the European Regional Development Fund (ERDF) [PON03PE_00024_1]
  7. ALForLab project - National Operational Program for Research and Competitiveness (PON R&C), through the national resource (Revolving Fund-Cohesion Action Plan (CAP) MIUR)

向作者/读者索取更多资源

Understanding the dynamics of organic carbon mineralization is fundamental in forecasting biosphere to atmosphere net carbon ecosystem exchange (NEE). With this perspective, we developed 3D-CMCC-PSM, a new version of the hybrid process based model 3D-CMCC FEM where also heterotrophic respiration (Rh) is explicitly simulated. The aim was to quantify NEE as a forward problem, by subtracting ecosystem respiration (Reco) to gross primary productivity (GPP). To do so, we developed a simplification of the soil carbon dynamics routine proposed in the DNDC (DeNitrification-DeComposition) computer simulation model. The method calculates decomposition as a function of soil moisture, temperature, state of the organic compartments, and relative abundance of microbial pools. Given the pulse dynamics of soil respiration, we introduced modifications in some of the principal constitutive relations involved in phenology and littering sub-routines. We quantified the model structure-related uncertainty in NEE, by running our training simulations over 1000 random parameter-sets extracted from parameter distributions expected from literature. 3D-CMCC-PSM predictability was tested on independent time series for 6 Fluxnet sites. The model resulted in daily and monthly estimations highly consistent with the observed time series. It showed lower predictability in Mediterranean ecosystems, suggesting that it may need further improvements in addressing evapotranspiration and water dynamics.

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