Grimm, A. G. 2011. Lidar-Based of understory bird habitat in a tropical forest. MS Thesis. University of Michigan, Ann Arbor.

            In this thesis, the author used a combination of field-based data and full-waveform LiDAR data, as well as presence bird data, to study the relationships between presence of understory birds and the diversity and structure of a forest at La Selva Biological Station in Costa Rica. The author used MAXENT to build habitat models, and they were validated using a jackknife approach. While in particular cases, the most important variables for bird distribution were different, in general variables such as canopy height, elevation, and distance to edge, predicted better the bird distribution than understory-specific metrics. Finally, results show that models which included canopy high profile metrics performed better than those that did not included, suggesting that LiDAR based habitat models can be improved by adding filed-based data.