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Economics of risk and tipping points: approaches to valuing forest resilience

Home Research Economics of risk and tipping points: approaches to valuing forest resilience

Summary

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The report provides a review of economic approaches to risk and uncertainty, tipping points and resilience. The review is motivated by increasing risk and uncertainty in forestry related to climate change and other factors, and the need to take them into account in making forest planning and management decisions. Ignoring risk and uncertainty could be expected to result in suboptimal choices, inefficient use of resources and poor investments decisions.

An overarching aim of the study is to consider how the tools reviewed could help in valuing resilience in forestry.

Research objectives

Specific objectives for this study are:

  1. To review major sources of risks and their associated magnitudes for provision of forest ecosystem services (e.g. timber provision, carbon sequestration, biodiversity and recreation) and resilience. Risks may include economic sources (e.g.: changes in timber prices, interest rates, ect), and ecological sources (e.g. tree growth rates and mortality affected by climate change, pests and diseases, wind and fire risks, etc.)
  2. To identify the most probable scenarios (including minimum and maximum boundaries) for various risks over the next 50 or 100 years.
  3. To identify and review the most useful existing economic methods, tools and models that could be used for valuing forest resilience and ecosystem services in the presence of risk.

Results 

The review found that there are currently no universally accepted definitions for risk, uncertainty and resilience, although there is more agreement on defining tipping points or critical thresholds. For the purposes of this study, risk is defined as a measure encompassing the probability and expected impact of uncertain events in the future, with uncertainty conceptualised as a set of probabilities of different potential future states.

Resilience is a comparatively new concept that can be especially difficult to define as it is multidimensional, with potentially rich social content and context. From an ecological perspective, resilience can be defined as the amount of disturbance that an ecosystem can withstand without changing self-organized processes and structures before flipping into a different equilibrium. Tipping points are defined as critical points or zones where relatively rapid change occurs from one stable state to another with a small change in conditions. However, there generally appears to be insufficient evidence at present to identify tipping points in forest ecosystems, and how they will be affected by climate change. Some very preliminary work is reported but much more basic field work and data collection are required.

The review of economic approaches to risk and uncertainty found that a variety of tools are available for modelling, including some novel developments such as robust optimisation. However, there have been relatively few applications in forestry economics to date.

While no simple prescriptive answer can be given to the question of which economic modelling approach to risk and uncertainty should be chosen in each particular case, general recommendations are:

  1. Consider modelling risk and uncertainty for problems where their influence is not negligible. [!]
  2. The best approach to use will depend on factors such as the scale and type of problem and the nature of the uncertainty, as well as the availability of resources and skills, etc.
  3. At a minimum, apply a scenarios and sensitivity analysis approach.
  4. Where the problem warrants more in-depth analysis of issues of risk and uncertainty, select a relatively well tested approach initially, e.g., mean-variance portfolio. Others include (i) stochastic dynamic programming and related real option approaches – suitable for optimising a harvesting schedule; (ii) Markov Decision Process and related simulation approaches (Monte-Carlo and Markov Chain Monte-Carlo) – suitable for complex forest growth and dynamic simulation; and iii) Bayesian statistics – suitable for situations where a process of learning about the problem occurs over time and so reduces uncertainty of probability estimates of different potential future states and parameters.

A conceptual framework for the resilience valuation is proposed, while acknowledging the complexity of defining and measuring resilience which are not yet fully resolved. Future work will benefit from linkages with other ongoing research on resilience within Forest Research.

Contact

Vadim Saraev

Downloads

review_of_economic_models_for_quantifying_risk_and_uncertainty_in_forestry

(PDF, 0.75 MB)

Final project report. Recommended citation: Saraev, V. (2019) Review of economic models for quantifying risk and uncertainty in forestry. Forest Research, Final Report, Edinburgh, UK.

Research Status
completed
Contacts
Economist
Forestry Staff Saraev Vadim 02.2e16d0ba.fill 600x600 1
Funding & partners
  • Funded by Forestry Commission