Black-backed woodpecker habitat suitability mapping using conifer snag basal area estimated from airborne laser scanning

Abstract:

Occupancy and habitat suitability models for snag-dependent wildlife species are commonly defined as a function of snag basal area. Although critical for predicting or assessing habitat suitability, spatially distributed estimates of snag basal area are not generally available across landscapes at spatial scales relevant for conservation planning. This study evaluates the use of airborne laser scanning (ALS) to 1) identify individual conifer snags and map their basal area across a recently burned forest, and 2) map habitat suitability for a wildlife species known to be dependent on snag basal area, specifically the black-backed woodpecker (Picoides arcticus). This study focuses on the Rim Fire, a megafire that took place in 2013 in the Sierra Nevada Mountains of California, creating large patches of medium- and high-severity burned forest. We use forest inventory plots, single-tree ALS-derived metrics and Gaussian processes classification and regression to identify conifer snags and estimate their stem diameter and basal area. Then, we use the results to map habitat suitability for the black-backed woodpecker using thresholds for conifer basal area from a previously published habitat suitability model. Local maxima detection and watershed segmentation algorithms resulted in 75% detection of trees with stem diameter larger than 30 cm. Snags are identified with an overall accuracy of 91.8 % and conifer snags are identified with an overall accuracy of 84.8 %. Finally, Gaussian process regression reliably estimated stem diameter (R² = 0.8) using height and crown area. This work provides a fast and efficient methodology to characterize the extent of a burned forest at the tree level and a critical tool for early wildlife assessment in post-fire forest management and biodiversity conservation.