Habitat amount and connectivity in forest planning models: Consequences for profitability and compensation schemes

Abstract

Adjacency relationships are pervasive in forest planning problems, especially the ones related to the selection of habitat networks for biodiversity conservation. Two main approaches are applied in the planning of these conservation actions: i) selection grounded on the island biogeography theory, where connected habitats are preferred and ii) selection grounded in the habitat amount hypothesis, where the amount of habitat is enforced in local landscapes, regardless of their spatial distribution. Because the presence of connectivity requirements in the creation of habitat networks impose more stringent limitations on the search for optimal solutions, they are expected to cascade to the total benefit from harvesting revenues and, consequently, to the costs of the habitat networks. The ecological implications of these approaches have been investigated, whereas the economic consequences of imposing connectivity remain unclear. Here, I address this issue and investigate the costs of selecting habitat networks in multiple forest landscapes in central Europe, applying these two approaches. To this end, a conic optimization model is proposed, to find minimum cost allocations of forest reserves. Furthermore, a sensitivity analysis on the optimal allocation is conducted, regarding the size of the habitat network required and the level of heterogeneity in forest profitability within the landscapes. The results show that habitat networks amounting to 10% of the forest area may be created with up to 5.5% reduction in the total Net Present Value (NPV), with a higher cost when connectivity is imposed (6.5%). The cost of connectivity, however, may increase in landscapes with high heterogeneity in forest profitability and with the minimum amount of habitat required. In conclusion, habitat selection must be tailored to local conditions and weight the additional costs of imposing connectivity against the requirements of the target species and the expected ecological benefits.

Keywords: Forest biodiversity; Forest economics; Forest planning; Semidefinite programming.