Effect of disturbances on fuel loading, fire-mosaic, and interactions in managed forest landscape

This study focused on understanding the relationships between forest productivity, management, disturbance, fuel loading, and fire spreading for predicting long-term ecological effects of disturbances. The study objectives were to evaluate the effect of various forest ecosystem characteristics and management on fuel loading and fire spread through modelling. Specifically, I sought to identify the main factors influencing fuel loading in different ecosystems, to examine the possibility of developing a simple fuel loading model and the applicability of the developed model, and to evaluate the spatial heterogeneity of fuel loading on surface fire spread in the Chequamegon National Forest (CNF), Wisconsin. I found that productivity and decomposition were two dominant driving factors determining fuel loading. I learned that the amount of fuel loading in arid or cold regions would be affected more by climate change than that in other climate regions. A fuel loading model (EcoFL) developed in this project successfully predicted fuel loading in hardwood, red pine, and jack pine. EcoFL predicts fuel loading using the concept of ecosystem level aboveground productivity dynamics. This simple model reduced parameter needs for simulations, and it is advantageous in developing a landscape level model. I found that pattern of carbon allocation was as important as productivity and decomposition in fuel loading prediction. My results suggest that the magnitude and duration of productivity reduced by prescribed burning strongly influence the forest biomass under frequent prescribed burning. EcoFL was combined with geographical information system, a forest cover type map, and a forest age map to produce a fuel map to examine fire spread under different scenarios of fuel loading heterogeneity. Burned area was influenced by complex interactions between fire ignition location and heterogeneity of fuel maps. The results imply that we need to understand the interactions between fire spreading and pattern of fuel loading to interpret the results appropriately from coarse resolution fuel maps and to apply the results to landscape management. Future studies need to focus on assessing productivity recovery and carbon allocation patterns after fire and the interactions of resolution of spatial data and fire spreading prediction under alternative regions, fire types, vegetation types, and topography.