Thursday, August 6, 2009 - 9:20 AM

OOS 36-5: Using discrete return lidar data to map the distribution of snags, understory shrubs, and avian habitat suitability in a mixed conifer forest

Sebastian Martinuzzi1, Lee A. Vierling1, William A. Gould2, Jeff Evans3, Michael Falkowski1, Andrew Hudak4, and Kerri T. Vierling1. (1) University of Idaho, (2) International Institute of Tropical Forestry, (3) The Nature Conservancy, (4) USDA Forest Service

Background/Question/Methods  

The lack of maps depicting three-dimensional forest structure, particularly as pertaining to snags and understory shrub distribution, can be a major limitation for managing wildlife habitat in forests. Developing new techniques to map snags and understory shrubs using remote sensing data is therefore an important need. To address this, we first evaluated the use of laser altimetry (LiDAR) data for mapping presence/absence of understory shrubs and different snag diameters in a mixed-conifer 30,000 ha forest in Northern Idaho (USA). We used forest inventory plots, LiDAR-derived metrics, and the Random Forest algorithm to develop predictive models of presence/absence.    Second, we evaluated the use of these LiDAR data products for mapping wildlife habitat suitability, using four avian species with different habitat requirements (dusky flycatcher, Lewis’ woodpecker, downy woodpecker, and hairy woodpecker).  For this effort, we integrated our LiDAR-derived products of forest structure with available models of habitat suitability to derive a variety of species-habitat associations, and therefore to delineate habitat suitability patterns across the landscape.

Results/Conclusions  

When mapping understory shrub and snag classes for our first objective, we achieved overall and individual class accuracies between 73% and 95%. We found that the value of LiDAR resided in the ability to quantify 1) ecological variables that are known to influence the distribution of understory vegetation and snags, such as canopy cover, topography, and forest succession, and 2) direct structural metrics that indicate or suggest the presence of shrubs and snags, such as the percentage of vegetation returns in the lower strata of the canopy (for the shrubs) and the vertical heterogeneity of the forest canopy (for the snags). When applied to the second objective of wildlife habitat assessment, we found that these new LiDAR-based maps refined habitat predictions in ways not previously attainable. This study highlights new value of LiDAR for characterizing key forest structure components important for wildlife, and warrants further applications to other forested environments and wildlife species.  Our group is currently undertaking similar studies in various habitats to test the wider applicability of these approaches, and we discuss prospects for applying these structural analysis techniques developed in coniferous temperate forests to a diverse array of ecosystems occurring in tropical landscapes of Puerto Rico.