Linking substrate and habitat requirements of wood-inhabiting fungi to their regional extinction vulnerability

Abstract

Loss of old-growth forests and greatly reduced volumes of coarse dead wood in managed forests are the main reasons for the decline of many wood-inhabiting species in Europe and elsewhere. To assess the habitat requirements and extinction vulnerability of 13 polypore species associated mainly with spruce, their occurrences were recorded on 96 521 dead-wood objects in 331 stands along a regional gradient of forest utilization history across southern-middle boreal Finland. The substrates studied included a variety of tree species and dead-wood qualities investigated in both unmanaged and managed stands at different successional stages. Hierarchical logistic regression models were constructed to analyze the relationships between the occurrence probability of individual species and variables at the substrate, stand and regional scales. The substrate preferences of the polypore species studied overlapped, since most of them favored large-diameter spruce logs in mid-decay stages. However, only a few species were restricted to this substrate. Other species were able to use a wider range of host tree species and qualities of dead wood, including man-made substrates that are abundant in managed forests (logging residues and stumps). Species confined to logs had a significantly lower occurrence probability in regions with the longest and most intensive forest use history. Species less specialized in their resource use showed no decline or the opposite trend. Loss of threatened species is likely if the preservation of old-growth forests is not combined with conservation measures in managed forests. Increasing extraction of logging residues and stumps for biofuel may cause non-threatened species to decline by reducing substrate qualities utilized by them. The hierarchical models predicted a considerable part of the variation in Species' occurrence probabilities, and therefore provide powerful tools for setting quantitative targets for management.