Sensitivity and uncertainty analysis from a coupled 3-PG and soil organic matter decomposition model

Georgios Xenakis, Duncan Ray and Maurizio Mencuccini

Ecological Modelling, 2008, vol. 219, issue 1, 1-16

Abstract: 3-PG [Landsberg, J.J., Waring, R.H., 1997. A generalised model of forest productivity using simplified concepts of radiation-use efficiency, carbon balance and partitioning. Forest Ecol. Manage. 95, 209–228] is a process-based model using simplified physiological concepts such as light use efficiency, a constant ratio between net and gross primary production and a simple stand nutritional status parameter. This last parameter is commonly adjusted manually to fit observations, based on data from field surveys. It has been shown that nutritional status has a significant effect on estimated gross and net productivity and it has been suggested that the introduction of a soil sub-model could overcome such problems. This paper introduces a soil organic matter decomposition model within the routines of 3-PG. ICBM/2N (Introductory Carbon Balance Model [Andrén, O., Kätterer, T., 1997. ICBM: the introductory carbon balance model for exploration of soil carbon balance. Ecol. Appl. 7, 1226–1236]) was chosen because it operates at a level of complexity similar to 3-PG. The new model 3-PGN (3-PG Nitrogen) includes three soil carbon and three soil nitrogen pools with eleven additional parameters. This approach provides a new way to account for soil nutritional status within 3-PGN by introducing a fertility rating that varies over the life of a stand. We present the integrated model and describe the basic concepts of the integration. The model has been calibrated and tested for commercial plantations of Scots pine (Pinus sylvestris L.) in Scotland. An uncertainty analysis was performed based on a Bayesian framework using Monte Carlo simulations and a sensitivity analysis to understand the model’s feedbacks and interactions between parameters and outputs. The results show that the least uncertain parameters were the most sensitive, having the greatest effect on many of 3-PGN’s outputs, including quantum yield efficiency, specific leaf area and foliage:stem biomass partitioning ratio. Although the soil sub-model had no direct effect on productivity, strong non-linear relationships were found between many of the soil parameters and 3-PGN outputs. Root turnover rate was found to be the most uncertain parameter, whereas the ratio of net to gross primary production was the least. Finally, through the validation procedure it was shown that 3-PG’s self-thinning routine may cause problems when predicting the number of stems in stands with low fertility.

Keywords: 3-PG; ICBM; Pinus sylvestris L.; Bayesian calibration; Uncertainty; Sensitivity analysis; Monte Carlo Markov Chain (search for similar items in EconPapers)
Date: 2008
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Citations: View citations in EconPapers (14)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:ecomod:v:219:y:2008:i:1:p:1-16

DOI: 10.1016/j.ecolmodel.2008.07.020

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