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A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration

Author

Listed:
  • Wang, Weile
  • Ichii, Kazuhito
  • Hashimoto, Hirofumi
  • Michaelis, Andrew R.
  • Thornton, Peter E.
  • Law, Beverly E.
  • Nemani, Ramakrishna R.

Abstract

The increasing complexity of ecosystem models represents a major difficulty in tuning model parameters and analyzing simulated results. To address this problem, this study develops a hierarchical scheme that simplifies the Biome-BGC model into three functionally cascaded tiers and analyzes them sequentially. The first-tier model focuses on leaf-level ecophysiological processes; it simulates evapotranspiration and photosynthesis with prescribed leaf area index (LAI). The restriction on LAI is then lifted in the following two model tiers, which analyze how carbon and nitrogen is cycled at the whole-plant level (the second tier) and in all litter/soil pools (the third tier) to dynamically support the prescribed canopy. In particular, this study analyzes the steady state of these two model tiers by a set of equilibrium equations that are derived from Biome-BGC algorithms and are based on the principle of mass balance. Instead of spinning-up the model for thousands of climate years, these equations are able to estimate carbon/nitrogen stocks and fluxes of the target (steady-state) ecosystem directly from the results obtained by the first-tier model. The model hierarchy is examined with model experiments at four AmeriFlux sites. The results indicate that the proposed scheme can effectively calibrate Biome-BGC to simulate observed fluxes of evapotranspiration and photosynthesis; and the carbon/nitrogen stocks estimated by the equilibrium analysis approach are highly consistent with the results of model simulations. Therefore, the scheme developed in this study may serve as a practical guide to calibrate/analyze Biome-BGC; it also provides an efficient way to solve the problem of model spin-up, especially for applications over large regions. The same methodology may help analyze other similar ecosystem models as well.

Suggested Citation

  • Wang, Weile & Ichii, Kazuhito & Hashimoto, Hirofumi & Michaelis, Andrew R. & Thornton, Peter E. & Law, Beverly E. & Nemani, Ramakrishna R., 2009. "A hierarchical analysis of terrestrial ecosystem model Biome-BGC: Equilibrium analysis and model calibration," Ecological Modelling, Elsevier, vol. 220(17), pages 2009-2023.
  • Handle: RePEc:eee:ecomod:v:220:y:2009:i:17:p:2009-2023
    DOI: 10.1016/j.ecolmodel.2009.04.051
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    References listed on IDEAS

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    1. Mo, Xingguo & Chen, Jing M. & Ju, Weimin & Black, T. Andrew, 2008. "Optimization of ecosystem model parameters through assimilating eddy covariance flux data with an ensemble Kalman filter," Ecological Modelling, Elsevier, vol. 217(1), pages 157-173.
    2. Federico Magnani & Maurizio Mencuccini & Marco Borghetti & Paul Berbigier & Frank Berninger & Sylvain Delzon & Achim Grelle & Pertti Hari & Paul G. Jarvis & Pasi Kolari & Andrew S. Kowalski & Harry La, 2007. "The human footprint in the carbon cycle of temperate and boreal forests," Nature, Nature, vol. 447(7146), pages 849-851, June.
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    1. Hidy, D. & Barcza, Z. & Haszpra, L. & Churkina, G. & Pintér, K. & Nagy, Z., 2012. "Development of the Biome-BGC model for simulation of managed herbaceous ecosystems," Ecological Modelling, Elsevier, vol. 226(C), pages 99-119.
    2. Song, Xiaodong & Bryan, Brett A. & Almeida, Auro C. & Paul, Keryn I. & Zhao, Gang & Ren, Yin, 2013. "Time-dependent sensitivity of a process-based ecological model," Ecological Modelling, Elsevier, vol. 265(C), pages 114-123.
    3. Garcia, Elizabeth S. & Tague, Christina L. & Choate, Janet S., 2016. "Uncertainty in carbon allocation strategy and ecophysiological parameterization influences on carbon and streamflow estimates for two western US forested watersheds," Ecological Modelling, Elsevier, vol. 342(C), pages 19-33.

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