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Calibration of the FullCAM model for Australian native vegetation

Author

Listed:
  • Forrester, David I.
  • England, Jacqueline R.
  • Pasut, Chiara
  • Paul, Keryn I.
  • Bennett, Lauren T.
  • Eastaugh, Chris
  • Fairman, Thomas
  • Fedrigo, Melissa
  • Gosper, Carl R.
  • Kasel, Sabine
  • Lewis, Tom
  • Marunda, Crispen
  • Neldner, Victor J.
  • Ngugi, Michael R.
  • O’Donnell, Alison
  • Page, Gerald F.M.
  • Prober, Suzanne M.
  • Richards, Anna E.
  • Suitor, Shaun
  • Volkova, Liubov
  • Weston, Christopher J.
  • Roxburgh, Stephen H.
  • Wang, Ying-Ping

Abstract

The Full Carbon Accounting Model (FullCAM) simulates carbon (C) pools of live biomass, standing dead mass, debris and soil, the flows among them and the atmosphere, and the influences of fire and harvesting disturbances under Australian conditions. It is regularly used by governments, landowners, companies and researchers, at continental, regional and local scales. Recently, FullCAM was calibrated for seven categories of native tropical savanna vegetation. However, for non-savanna native vegetation, calibrated parameters are available for only two general vegetation categories, based on whether the annual rainfall exceeds or falls below 500 mm. These two categories are too broad to capture the large range of growth conditions, vegetation structures and species assemblages that occur across Australia’s native woody vegetation. Here, our objective was to improve FullCAM’s ability to model variation in C pools and post-disturbance recovery among eight native vegetation categories, from shrublands to rainforests, for which there were differences in biomass allocation, litterfall and/or decomposition. To do this, we calibrated FullCAM for each vegetation type, including 14 parameters that were calculated directly from field observations and 17 that were calibrated using a dataset containing about 9300 field plots with measurements of at least one woody vegetation C stock. New parameters (compared with the two general parameter sets) reduced bias from 77 to 25 % (averaged across C stocks), and root mean square error from 44 to 30 Mg C ha-1. Model accuracy could be further improved (i) by focusing on sites with a known disturbance history, (ii) calibrating as many vegetation categories as possible (instead of eight categories generalising across many species), and (iii) adding more detail to growth calculations to quantify factors that may not be adequately represented by FullCAM’s growth equation.

Suggested Citation

  • Forrester, David I. & England, Jacqueline R. & Pasut, Chiara & Paul, Keryn I. & Bennett, Lauren T. & Eastaugh, Chris & Fairman, Thomas & Fedrigo, Melissa & Gosper, Carl R. & Kasel, Sabine & Lewis, Tom, 2025. "Calibration of the FullCAM model for Australian native vegetation," Ecological Modelling, Elsevier, vol. 508(C).
  • Handle: RePEc:eee:ecomod:v:508:y:2025:i:c:s0304380025001899
    DOI: 10.1016/j.ecolmodel.2025.111204
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    References listed on IDEAS

    as
    1. Forrester, David I. & England, Jacqueline R. & Paul, Keryn I. & Roxburgh, Stephen H., 2024. "Sensitivity analysis of the FullCAM model: Context dependency and implications for model development to predict Australia's forest carbon stocks," Ecological Modelling, Elsevier, vol. 489(C).
    2. Unkovich, Murray & Baldock, Jeff & Farquharson, Ryan, 2018. "Field measurements of bare soil evaporation and crop transpiration, and transpiration efficiency, for rainfed grain crops in Australia – A review," Agricultural Water Management, Elsevier, vol. 205(C), pages 72-80.
    3. repec:plo:pone00:0081246 is not listed on IDEAS
    4. Forrester, David I. & Tang, Xiaolu, 2016. "Analysing the spatial and temporal dynamics of species interactions in mixed-species forests and the effects of stand density using the 3-PG model," Ecological Modelling, Elsevier, vol. 319(C), pages 233-254.
    5. Josep G. Canadell & C. P. (Mick) Meyer & Garry D. Cook & Andrew Dowdy & Peter R. Briggs & Jürgen Knauer & Acacia Pepler & Vanessa Haverd, 2021. "Multi-decadal increase of forest burned area in Australia is linked to climate change," Nature Communications, Nature, vol. 12(1), pages 1-11, December.
    6. Gupta, Rajit & Sharma, Laxmi Kant, 2019. "The process-based forest growth model 3-PG for use in forest management: A review," Ecological Modelling, Elsevier, vol. 397(C), pages 55-73.
    7. Mark A. Adams & Mathias Neumann, 2023. "Litter accumulation and fire risks show direct and indirect climate-dependence at continental scale," Nature Communications, Nature, vol. 14(1), pages 1-11, December.
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