PRAFOR: Probabilistic drought Risk Analysis for FORested landscapes

Project PRAFOR started 1 February 2020 and runs for two years. The aim of the project is to improve theory for risk analysis, apply it to forests in the UK, Spain and Finland, and improve an existing decision-support system.

Five organisations collaborate in PRAFOR:

  • UK Centre for Ecology & Hydrology (UKCEH; Marcel van Oijen, David Cameron)
  • Biomathematics and Statistics Scotland (BioSS; Mark Brewer)
  • Forest Research UK (FR; Mike Perks, James Morison, Georgios Xenakis)
  • University of Alcalá in Madrid, Spain (Miguel Zavala)
  • Natural Resources Institute Finland in Helsinki (Luke; Mikko Peltoniemi)

Risk (R) is the expectation of loss. We showed previously how risk can be decomposed as the product of hazard probability (p[H]) and ecosystem vulnerability (V), such that R = p[H] V ( Project PRAFOR will build on this work using drought risk to coniferous forests as an example. The project work will be in seven steps:

1. Extend the existing risk analysis theory to include exposure (E) as extra component: R = p[H] E V.

2. Show how uncertainties in R, p[H], E and V can be quantified.

3. Apply the analysis to forested landscapes in UK, Spain, Finland.

4. Use process-based forest models BASFOR and 3PGN to identify determinants of V.

5. Identify possible actions that can reduce p[H], E and V in the three countries, and the costs of each action.

6. Use Bayesian decision theory to evaluate action portfolios, accounting for uncertainties in data and models.

7. Improve an existing forest decision support system (ESC-DSS; with the risk and uncertainty analysis.

Principle Investigator from project inception to Sept 2020 Marcel van Oijen introduces the project in this short video
Project Partners:
Biomathematics and Statistics Scotland – Statistical Methodology:
Forest Research – Climate Change Adaptation:
University of Alcalá – Forest Ecology and Restoration:
Natural Resources Institute Finland – Boreal Green Bioeconomy:
Link to the project page on the UKRI Gateway to Research