Lidar-derived canopy architecture predicts Brown Creeper occupancy of two western coniferous forests

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Abstract

In western conifer-dominated forests where the abundance of old-growth stands is decreasing, species such as the Brown Creeper (Certhia americana) may be useful as indicator species for monitoring the health of old-growth systems because they are strongly associated with habitat characteristics associated with old growth and are especially sensitive to forest management. Light detection and ranging (lidar) is useful for acquiring fine-resolution, three-dimensional data on vegetation structure across broad areas. We evaluated Brown Creeper occupancy of forested landscapes by using lidar-derived canopy metrics in two coniferous forests in Idaho. Density of the upper canopy was the most important variable for predicting Brown Creeper occupancy, although mean height and height variability were also included in the top models. The upper canopy was twice as dense and the mean height was almost 50% higher at occupied than at unoccupied sites. Previous studies have found indicators of canopy density to be important factors for Brown Creeper habitat; however, this represents the first time that lidar data have been used to examine this relationship empirically through the mapping of the upper canopy density that cannot be continuously quantified by field-based methods or passive remote sensing. Our model's performance was classified as "good" by multiple criteria. We were able to map probabilities of Brown Creeper occupancy in ~50 000 ha of forest, probabilities that can be used at the local, forest-stand, and landscape scales, and illustrate the potential utility of lidar-derived data for studies of avian distributions in forested landscapes. © The Cooper Ornithological Society 2013.

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Vogeler, J. C., Hudak, A. T., Vierling, L. A., & Vierling, K. T. (2013). Lidar-derived canopy architecture predicts Brown Creeper occupancy of two western coniferous forests. Condor, 115(3), 614–622. https://doi.org/10.1525/cond.2013.110082

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