Lidar is a remote sensing tool that can describe both the vertical and horizontal distribution of vegetation, allowing researchers to quantify habitat complexity for species residing in forest canopies. USGS researchers and collaborators used lidar data to estimate occupancy probability for the federally threatened marbled murrelet in Oregon Coast Range forests managed by the Bureau of Land Management and the Oregon Department of Forestry. Their goal was to provide an improved estimate of the availability of nesting habitat by developing occupancy maps based on refined habitat measurement. Researchers developed a model that included five lidar-derived variables describing canopy structure that reflect age-related forest characteristics and are consistent with murrelet nesting ecology. The model resulted in a more accurate representation of murrelet nesting habitat when compared to a model with variables estimated using traditional methods. The refined measures of forest structure selected by murrelets for nesting are useful for estimating availability of nesting habitat, which is an important consideration in forest management decisions, particularly the siting of restoration and timber harvest projects. Lidar-based occupancy models are now being developed for northern spotted owls and red tree voles, the owls’ principal prey species.