Stephen R. Hale
The Auk 123 (4), 1038-1051, (1 October 2006) https://doi.org/10.1642/0004-8038(2006)123[1038:USITMD]2.0.CO;2
KEYWORDS: Bicknell's Thrush, Catharus bicknelli, distribution mapping, Geographic Information System, habitat modeling, logistic regression, remote sensing
Satellite imagery was used to model the distribution and abundance of Bicknell's Thrush (Catharus bicknelli) in the White Mountains of New Hampshire. Image-derived data for live softwood shrub density, standing dead-tree basal area, distance to nearest fir-shrub cover type, along with a digital elevation model and point-count data, were used to supply regressor estimates in a multivariate logistic habitat model that was constructed from field vegetation sampling and point-count data. Spatially explicit predictions of probability of Bicknell's Thrush presence were made for each 28.5 × 28.5 m-pixel covering 70,000 ha. A model validation procedure using observations independent from model calibration revealed no difference (P > 0.05) between modeled and observed estimates of Bicknell's Thrush presence within probability deciles 0 to <0.1, 0.1 to <0.2, 0.2 to <0.3, 0.3 to <0.4, 0.5 to <0.6, and 0.6 to <0.7 with respective densities (40 ha−1) of 0.5, 1.6, 2.8, 4.1, 7.3, and 9.4. Transforming probabilities into relative abundance produced an estimated 4,900 Bicknell's Thrushes across the study area. Habitats supporting the highest density of Bicknell's Thrushes were predicted to be at the uppermost elevations. However, abundance estimates decreased even as density increased, owing to decreasing amounts of habitat area with increasing elevation, and suggested that lower-elevation, low-density habitats may support a significant fraction of Bicknell's Thrushes.
Utilisation de l'Imagerie Satellitaire afin de Modéliser la Distribution et l'Abondance de Catharus bicknelli dans les White Mountains du New Hampshire