MODELING ABUNDANCE EFFECTS IN DISTANCE SAMPLING

• DOI: 10.1890/03-3127
• Publication Date: 2007-06-04T23:31:42Z
• Authors: J. Andrew Royle; Deanna K. Dawson; Scott Bates
• Keywords: Distance sampling; Abundance estimation; Poisson sampling; Basal area; Understory

Distance-sampling methods are commonly used in studies of animal populations to estimate population density. A common objective such is evaluate the relationship between abundance or density and covariates that describe habitat other environmental influences. However, little attention has been focused on modeling covariate effects conventional distance-sampling models. In this paper we propose a model accommodates abundance. The based specification likelihood at level sample unit terms local (for each sampling unit). This augmented with Poisson regression for parameterized available covariates. Maximum-likelihood estimation detection parameters integrated likelihood, wherein removed from by integration. We provide an example using avian point-transect data Ovenbirds (Seiurus aurocapillus) collected protocol two measures structure (understory cover basal area overstory trees). yields sensible description (positive effect understory cover, negative area) Ovenbird can be management populations.