Assessing relationships between lidar-derived vegetation structure and butterfly density to improve butterfly habitat mapping

The assessment of both local and landscape level vegetation features is essential when comparing species presence and density to habitat characteristics. LiDAR remote sensing provides highly detailed information quantifying vegetation structural parameters that are often indicative of habitat quality at both local and landscape scales. Previous studies using LiDAR data for habitat assessment have compared vegetation structure to various species, but few have integrated both local and landscape scale data. This study evaluates the efficacy of pairing LiDAR data with field-based habitat measurements to characterize species-habitat relationships for four butterfly species in Northern Idaho, USA. LiDAR data was employed to characterize landscape-scale forest structural attributes, and field measurements were taken to quantify local habitat characteristics that may influence the butterfly species under investigation. According to a non-metric multi dimensional scaling ordination, the four butterflies addressed in this study are distributed into two groups, one more associated with LiDAR-derived vegetation metrics and the other more associated with percent cover of host plant and landscape-scale landcover characteristics. We conclude that incorporating LiDAR data in habitat-species relationship studies may allow for more in-depth evaluations of habitat quality and structure across large spatial extents.