Journal of Forest Economics > Vol 34 > Issue 1-2

Uncertainty of Carbon Economy Using the Faustmann Model

Rasoul Yousefpour, University of Freiburg, Germany, rasoul.yousefpour@ife.uni-freiburg.de Andrey L. D. Augustynczik, University of Freiburg, Germany,
 
Suggested Citation
Rasoul Yousefpour and Andrey L. D. Augustynczik (2019), "Uncertainty of Carbon Economy Using the Faustmann Model", Journal of Forest Economics: Vol. 34: No. 1-2, pp 99-128. http://dx.doi.org/10.1561/112.00000444

Published: 07 Aug 2019
© 2019 R. Yousefpour and A. L. D. Augustynczik
 
Subjects
 
Keywords
Bayesian statisticsRobust Decision-makingDeep uncertaintyClimate changeCompromise programmingCarbon economyCOP21Forest Policy Design
 

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In this article:
1. Introduction
2. Material and Methods
3. Results
4. Discussions and Conclusions
References

Abstract

Forest growth predictions are used to build expectations about the future economic performance of management decisions. Faustmann land expectation value (LEV) is a widely used criterion in forestry to evaluate a diversity of decision parameters, such as rotation age and thinning regimes. Most of the predictions and, consequently, expectations are based on emperical knowledge, assuming a steady state in climate and a deterministic forest growth approach. However, the climate may change to potentially different degrees in the coming decades, causing a dynamic and uncertain forest growth and carbon budget. Moreover, carbon economy in forestry, defined as opportunity cost of in situ carbon sequestration, can hardly be analysed using empirical models and calls for process-based forest biomass production models. Process-based models include numerous parameters and processes that embody some degree of uncertainty. The uncertainty of these parameters and climate state propagates over time to the final decision about carbon economy and optimal management solutions. Here we quantify this uncertainty using Bayesian inference and apply twelve different climate change scenarios to evaluate the forecasts of the process-based forest model 3-PG, to predict the growth of European beech (Fagus Sylvatica) in central european conditions as an example. The results show a strong influence of the model’s parameters uncertainty on the final decisions about timber based and carbon economy. The uncertainty triples if different climate change scenarios are applied as a source of deep uncertainty where no probability can be assigned to any scenario. To deal with deep uncertainty, a robust decision-making approach has been applied to find solutions with minimum regret or maximum value at risk regarding all scenarios. We conclude that communicating uncertainty is a fundamental issue for forestry economics under changing climate conditions, especially if carbon sequestration is an asset. The key message for designing global forest governance policy in the uncertain times of climate change will be the necessity to take into account both the uncertainty on the demand side, that is, socio-economic developments and regional population needs for forest ecosystem services such as wood, but also the uncertainty of the supply side and the inherent ecological uncertainties in predicting the forests’ growth, resources, and climatic conditions.

DOI:10.1561/112.00000444

Companion

Journal of Forest Economics, Volume 34, Issue 1-2 Special issue - State of the art methods to project forest carbon stocks: Articles Overiew
See the other articles that are part of this special issue.