Wood Fungi and Forest Fire

Abstract: Forest fires have been the major stand-replacing/modifying disturbance in boreal forests. To adapt to fire disturbance, different strategies have evolved. This thesis focuses on wood fungi, and the effect of forest fire on this organism group. In many ways it is a study on adaptation to forest fire, in concurrence with adaptation to dry open habitats. In Paper I we study increased heat resistance in  mycelia from species prevalent in fire prone environments. Fungi were cultivated on fresh wood and exposed to different temperatures. Species prevalent in fire affected habitats had a much higher survival rate over all combinations of time and temperature compared to species associated with other environments. Based on this results the competitiveness was tested after temperature stress (paper II), three fire associated species, were tested against three non fire associated species. All fire associated species had a clear advantage after heat treatment, conquering a larger volume of wood than its competitor. In paper III we studied the effect of heat shock on decomposition rate, 18 species was tested. Species were cultivated and monitored for CO2 accumulation for 8 weeks and then heat shocked. All species including non fire associated species seemed to up-regulate decomposition after heat shock, this response was more pronounced in fire associated species. To look at the possible effect of forest fire on population structure (Paper IV), we developed 29 SNP/INDELs for Phlebiopsis. gigantea. We amplified the marker containing fragments in 132 individuals of P. gigantea in 6 populations, 3 which were found in areas affected by forest fire and 3 in unaffected areas. We found no genetic structure in accordance to forest fire. However we detected geographic structure, which stands in contrast to earlier studies. This might be due to the method, using SNP´s and number of individuals in the study. Finally we collected cross-sections of decayed logs to evaluate the number of fungal species domains that are likely to be hit when drilling a saw-dust sample in a log. We used these estimates to simulate how many species that will be found by a certain number of samples. We found that in 99% of the