Epsilon Open Archive

Abstract

Most boreal forests in North Europe are intensively managed, and the forest landscape is far from its natural stage leading to hundreds of species being threatened in Sweden alone. Reserves are established to protect biodiversity, but since the resources available for conservation do not cover all species in need of protection, effective prioritization is essential.

In this thesis, a reserve selection model based on a goal programming approach was developed, finding the optimal age composition of reserves in boreal Sweden under different prerequisites. Forest data were derived from the Swedish National Forest Inventory (NFI) and the amount of structural indicators (proxy for biodiversity) registered in the NFI were maximized while simultaneously reassuring that all indicators were represented. I wanted to investigate how reserve selection could be made more effective by considering: (1) cost, (2) subjective preferences, and (3) future biodiversity potential, where the development over time was simulated using the forest analysis and planning tool Heureka PlanWise. To evaluate species response to retained structures in young managed forest, lichen species richness on retained aspen trees was surveyed. Results show that young forest is a cost-effective alternative. The proportion of young forest varied from 46% when subjective preferences were considered, to 76% when only the future values were considered. The cost-effective models were contrasted with area-effective models to show the pros and cons with such approaches. The area-constrained models often selected a more or less large proportion of old forest (77% when subjective preferences were considered, but 13% when only future values were considered), and were more expensive but covered less area to reach the same biodiversity value. In the aspen study higher lichen species richness was found on the retained trees that had been exposed for a longer time, including easily dispersed species and species often found in old forest. Scientists alone cannot find the optimal reserve network, since it depends on the goals that are set by society and how success is valued. Decision makers have to integrate societal, ecological and economic data and balance short term and long term constraints in terms of cost and available area in order to design cost-effective conservation strategies.