Using stochastic dynamic programming to determine optimal fire management for Banksia ornata
‡Correspondence: Michael A. McCarthy, School of Botany, University of Melbourne, Parkville, VIC 3010, Australia (fax 61 3 9347 5460; firstname.lastname@example.org).
- 1 A model of the population dynamics of Banksia ornata was developed, using stochastic dynamic programming (a state-dependent decision-making tool), to determine optimal fire management strategies that incorporate trade-offs between biodiversity conservation and fuel reduction.
- 2 The modelled population of B. ornata was described by its age and density, and was exposed to the risk of unplanned fires and stochastic variation in germination success.
- 3 For a given population in each year, three management strategies were considered: (i) lighting a prescribed fire; (ii) controlling the incidence of unplanned fire; (iii) doing nothing.
- 4 The optimal management strategy depended on the state of the B. ornata population, with the time since the last fire (age of the population) being the most important variable. Lighting a prescribed fire at an age of less than 30 years was only optimal when the density of seedlings after a fire was low (< 100 plants ha−1) or when there were benefits of maintaining a low fuel load by using more frequent fire.
- 5 Because the cost of management was assumed to be negligible (relative to the value of the persistence of the population), the do-nothing option was never the optimal strategy, although lighting prescribed fires had only marginal benefits when the mean interval between unplanned fires was less than 20–30 years.