Selection of nature reserve networks

The Convention on Biological Diversity (Rio de Janeiro, 1992) addresses the need for establishing a system of protected areas and for developing guidelines for the establishment the protected areas. In Finland, Natura 2000 conservation programme was established for this purpose. In this thesis, different options for selecting and evaluating conservation areas are explored with data on boreal mires, semi-natural grasslands, herb-rich forests, old-growth forests and boreal lakes. Several taxa are used: beetles, bugs, polypores and vascular plants. Biodiversity is measured in terms of species richness, number of typical species, restricted range diversity, and taxonomic diversity based on a phylogenetic tree. The comparison of reserve networks showed that each biodiversity measure is usually maximised by a procedure based on the same measure as the selection criterion. The most species rich sites selected by a scoring procedure can be considered locally as richness hotspots. In general, scoring procedures were less efficient than heuristic methods and optimizing algorithms. A scoring procedure based on multiple criteria was the most inefficient option. A heuristic method appeared to be a good option when a priority order of sites was needed. Exact optimising algorithms can find optimal solutions to the reserve selection problems. In this study, heuristic and optimising algorithms were nearly equally efficient. Optimal networks of old growth forests for beetles, heteroptera and vascular plants supported one another relatively efficiently, but the protection of polypores required a different set of forests. The modern advances in information technology, e.g. geographical information systems (GIS), should be applied into reserve selection problems. The problems related to the selection of conservation areas are complicated, and the problem solving requires joint effort from experts in different biological areas. Research and education at universities play a key role if the recent research advances are to be applied in decision making.