Balancing conservation and economic gain: a dynamic programming approach

We optimize the trade-off between economic and ecological concerns in conse rvation biology by using a novel method to link a spatially explicit indivi dual-based model to a dynamic programming model. To date, few optimality mo dels have been presented to optimize this trade-off, especially when the co mmon currency cannot be easily measured in dollars. We use a population sim ulation model (e.g. spatially explicit individual-based model) to model a h ypothetical forest bird population's response to different cutting and plan ting regimes. We then link these results to a dynamic programming model to determine the optimal choice a manager should make at each time step to min imize revenue foregone by not harvesting timber while maintaining a given p opulation of birds. Our results show that if optimal management choices are made further back in time, future (terminal) reward may be greater. As the end of the management period approaches, past management practices influen ce the terminal reward more than future practices can. Thus if past revenue lost is high, the future reward will be low as compared to when past reven ue lost is low. The general strategy of setting some minimum viable populat ion size and then using a population simulator linked to a dynamic programm ing model to ask how to maintain such a population size with minimum econom ic loss should have nearly universal applicability in conservation biology. (C) 1999 Elsevier Science B.V. All rights reserved.