LiDAR as a Tool to Characterize Wildlife Habitat: California Spotted Owl Nesting Habitat as an Example

Abstract

Abstract We show the use of an emerging technology, airborne light detection and ranging (LiDAR), to assess forest wildlife habitat by showing how it can improve the characterization of California spotted owl (Strix occidentalis occidentalis) nesting habitat. Large residual trees are important elements for many wildlife species and often, apparently, facilitate selection of habitat by spotted owls. However, we currently lack the ability to identify such trees over large spatial scales. We acquired multiple-return, high-resolution LiDAR data for a 107.1-km2 area in the central Sierra Nevada, California. We surveyed for spotted owls within this area during 2007–2009 and located four nest trees. We then used the LiDAR data to measure the number, density, and pattern of residual trees (≥90-cm dbh) and to estimate canopy cover within 200 m of four nest trees. Nest trees were surrounded by large numbers of residual trees and high canopy cover. We believe that LiDAR would greatly benefit forest managers and scientists in the assessment of wildlife– habitat relationships and conservation of important wildlife species.