Assessing biodiversity conservation potential in the Nova Forest Alliance (NFA) land base using expert systems

This thesis developed a conservation assessment for identifying priority areas of high biodiversity value in the Nova Forest Alliance (NFA) using expert systems. The goals of this research were to provide a spatially explicit representation of conservation priorities with respect to biodiversity and land ownership patterns in the NFA, and provide a decision support framework that the NFA and other model forests can adopt. Three decision constraints were developed and assessed in the expert systems MARXAN and C-Plan. Two of these parameters assessed priorities using biodiversity targets, the third assessed changes to sites available within the planning domain. These expert systems were also assessed in terms of their utility in fulfilling the planning objectives of complementarity, flexibility, efficiency, and irreplaceability. Results indicate that current protected areas in the NFA are deficient in achieving conservation targets, and that Provincial Crown land sites can only partially fulfill conservation targets. Both expert systems provided a complementary approach in assessing priority sites in the NFA; but both differ in assessing irreplaceability and efficiency. Finally, the majority of sites selected in both the optimal and irreplaceability assessment were consistently found to be in the small-medium private ownership class, suggesting that conservation initiatives should target small-medium private land owners.