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Knowledge update in adaptive management of forest resources under climate change: a Bayesian simulation approach

Abstract

Context

We develop a modelling concept that updates knowledge and beliefs about future climate changes, to model a decision-maker’s choice of forest management alternatives, the outcomes of which depend on the climate condition.

Aims

Applying Bayes’ updating, we show that while the true climate trajectory is initially unknown, it will eventually be revealed as novel information become available. How fast the decision-maker will form firm beliefs about future climate depends on the divergence among climate trajectories, the long-term speed of change, and the short-term climate variability.

Methods

We simplify climate change outcomes to three possible trajectories of low, medium and high changes. We solve a hypothetical decision-making problem of tree species choice aiming at maximising the land expectation value (LEV) and based on the updated beliefs at each time step.

Results

The economic value of an adaptive approach would be positive and higher than a non-adaptive approach if a large change in climate state occurs and may influence forest decisions.

Conclusion

Updating knowledge to handle climate change uncertainty is a valuable addition to the study of adaptive forest management in general and the analysis of forest decision-making, in particular for irreversible or costly decisions of long-term impact.

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Acknowledgments and funding

This study was conducted as part of the project MOTIVE ‘MOdels for adapTIVE forest management’ funded by the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 226544. JBJ and BJT further acknowledge the support of the Danish National Science foundation.

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Authors

Corresponding author

Correspondence to Rasoul Yousefpour.

Additional information

Handling Editor: Marc Hanewinkel

Contribution of the co-authors

Rasoul Yousefpour: Corresponding Author, Developing the conceptual model, Analysis of the example, Providing tables and figures, Writing the manuscript, Supervising preparation of the manuscript according to the comments of all co-authors, Setting up the MS according to the format of AFS Jette Bredahl Jacobsen, Henrik Meilby, and Bo Jellesmark Thorsen: Developing the conceptual model and analysis, and writing the manuscript.

Appendix A

Appendix A

Table 5.

Table 5 Sensitivity analysis of beliefs update to observation variances

Appendix B

Table 6.

Table 6 Land expectation value (LEV) of optimal decisions based on Bayesian updating

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Yousefpour, R., Jacobsen, J.B., Meilby, H. et al. Knowledge update in adaptive management of forest resources under climate change: a Bayesian simulation approach. Annals of Forest Science 71, 301–312 (2014). https://doi.org/10.1007/s13595-013-0320-x

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Keywords

  • Subjective risk
  • Belief update
  • Adaptive forest management
  • Monte Carlo simulation
  • Species selection