Using Satellite and Airborne LiDAR to Model Woodpecker Habitat Occupancy at the Landscape Scale

Abstract

Incorporating vertical vegetation structure into models of animal distributions can improve understanding of the patterns and processes governing habitat selection. LiDAR can provide such structural information, but these data are typically collected via aircraft and thus are limited in spatial extent. Our objective was to explore the utility of satellite-based LiDAR data from the Geoscience Laser Altimeter System (GLAS) relative to airborne-based LiDAR to model the north Idaho breeding distribution of a forest-dependent ecosystem engineer, the Red-naped sapsucker (Sphyrapicus nuchalis). GLAS data occurred within ca. 64 m diameter ellipses spaced a minimum of 172 m apart, and all occupancy analyses were confined to this grain scale. Using a hierarchical approach, we modeled Red-naped sapsucker occupancy as a function of LiDAR metrics derived from both platforms. Occupancy models based on satellite data were weak, possibly because the data within the GLAS ellipse did not fully represent habitat characteristics important for this species. The most important structural variables influencing Red-naped Sapsucker breeding site selection based on airborne LiDAR data included foliage height diversity, the distance between major strata in the canopy vertical profile, and the vegetation density near the ground. These characteristics are consistent with the diversity of foraging activities exhibited by this species. To our knowledge, this study represents the first to examine the utility of satellite-based LiDAR to model animal distributions. The large area of each GLAS ellipse and the non-contiguous nature of GLAS data may pose significant challenges for wildlife distribution modeling; nevertheless these data can provide useful information on ecosystem vertical structure, particularly in areas of gentle terrain. Additional work is thus warranted to utilize LiDAR datasets collected from both airborne and past and future satellite platforms (e.g. GLAS, and the planned IceSAT2 mission) with the goal of improving wildlife modeling for more locations across the globe.

Airborne Lidar for Woodland Habitat Quality Monitoring: Exploring the Significance of Lidar Data Characteristics when Modelling Organism-Habitat Relationships

“…Measures of forest vertical structure (e.g., mean and standard deviation of canopy height) and horizontal patterns of vertical structure (assessed by both semivariograms and lacunarity analysis), together with elevation, land-cover and hydrography data were found useful in predictive distribution modelling for the red-cockaded woodpecker (Picoides borealis, Vieillot) in a forested catchment in North Carolina [31]. For the red-naped sapsucker (Sphyrapicus nuchalis) in northern Idaho, key airborne lidar variables for predicting breeding site selection were foliage height diversity, the distance between major strata in the canopy vertical profile, and vegetation density close to the ground [17]. Moving away from birds as the focal species, in a study of the Pacific fisher in the Sierra Nevada Mountains, California, tree height and slope were shown to be important variables within a 20 m radius of a denning tree, but forest structure and complexity became more important between 20 m and 50 m [19].…”

“…This makes use of lidar data as an explanatory tool to increase understanding (and quantification) of resource selection by species of known distribution [13]. Such studies have most frequently focussed on bird species [14][15][16][17], but with a growing number examining mammals, such as the bald-faced saki monkey (Pithecia irrorata) [18], Pacific fisher (Martes pennanti) [19], moose (Alces alces) [20], and red squirrel (Sciurus vulgaris) [21].…”

Elk resource selection patterns in a semiarid riparian corridor

“…We used discrete return Light Detection and Ranging (LiDAR) to determine structural characteristics of vegetation important for elk hiding and thermal cover (Hill and Thomson , Vierling et al ). The LiDAR data were collected from aircraft by the United States Army Corps of Engineers when foliage was present in 2010.…”

A review of the role of active remote sensing and data fusion for characterizing forest in wildlife habitat models

“…The typical measures derived from both discrete and waveform airborne lidar were comparable, usually characterizing some aspect of canopy height, density, or the distribution of vegetation within specific height strata. The only study exploring spaceborne lidar for habitat assessment applications was Vierling et al (2013) who compared the utility of discrete airborne lidar metrics with those derived from satellite-based Geoscience Laser Altimeter Systems (GLAS) lidar for quantifying red-naped sapsucker habitat relationships.…”