NASA’s Global Ecosystem Dynamics Investigation (GEDI) mission is space-based mission designed to measure three dimensional (3D) global forest structure. However, GEDI also produces large gaps between samples ­– which may cause issues for researchers that wish to use GEDI data to link habitat structure to biodiversity patterns/community functioning. To test whether these gaps in GEDI data cause serious biases in studies that aim to link forest structure to diversity patterns, we derived a suite of habitat structure indices using both GEDI data and similar remote sensing data taken from airplanes that didn’t have the gaps in the spatial coverage of the data. After calculating the two different sets of forest structural metrics (from both GEDI and airborne LiDAR) and modeling them against various measures of bird diversity, we found that structural metrics derived from GEDI data performed worse than airborne data when used to derive mechanistic relationships between habitat structure and bird diversity. However, we also found that when GEDI was used to predict bird diversity alongside other environmental metrics, GEDI data performed just as well as airborne data. These results demonstrate that researchers must exercise caution when using GEDI data to derive mechanistic understanding between structure and biodiversity.