Forest landscape management in a stochastic environment, with an application to mixed loblolly pine-hardwood forests

This paper seeks ways of managing forests for landscape diversity, tree species and size diversities and timber production in a stochastic environment. A Markov chain model was developed to describe stand transition between pre-defined states, with high-frequency shocks and rare natural catastrophes. Stochastic optimization was then used with this model to study the trade-off between landscape diversity and other management objectives. This approach was applied to the mixed loblolly pine (Pinus taeda L.) and hardwood forests in the southern United States. The results showed that natural catastrophes enhanced the diversity of the landscape, but impaired the tree species and size diversities. Following current management would generate high landscape diversity, but low timber productivity. A highly diverse landscape could be maintained while keeping the tree species and size diversities near the achievable maximum. But managing to maximize tree size diversity or species diversity would much decrease landscape diversity. The opportunity cost of preserving a highly diverse landscape was high in terms of foregone timber production.