The current Mountain Pine Beetle (MPB, Dendroctonius ponderosae) outbreakhas reached the highest population levels in recorded history, particularlyin British Columbia. Parks Canada has spent significant funds onmanagement actions aimed at stemming the infestation, but the effectivenessof these measures is difficult to determine with field work alone.Mathematical modelling is a useful tool in this work, as it can be used toinvestigate the effect of different management strategies without damage tothe landscape or economy. The goals of this study are 1) to understand theinteraction between intrinsic attack patterns and landscape heterogeneitiesin shaping the spread of the MPB infestation, and 2) to quantify the extentof control achieved by management activities used in Banff National Park(NP). I have developed a mathematical model of MPB populations using adiffusion-based approach incorporating MPB biology and attack dynamics andthe density and distribution of susceptible lodgepole pine trees. I haveused the model to simulate MPB population growth and dispersal and beetle-induced tree mortality in a homogeneous landscape. Building on this work,I will simulate the course of endemic and epidemic MPB infestations,including tree dynamics, in heterogeneous landscapes. Theoretical and reallandscapes will be drawn from Banff NP data. Management actions will beincluded in the model by modifying pheromone secretion and the spatialdensity of susceptible trees. The documented management and no-managementactions in Banff NP will be used to test and optimize the managementparameters in my study. I will use a suite of mathematical and statisticaltechniques to determine the impact of management actions, and closecollaboration with stakeholders will ensure the relevance of my results toparks management.