MODELING AVIAN ABUNDANCE FROM REPLICATED COUNTS USING BINOMIAL MIXTURE MODELS

By Marc Kéry, J. Andrew Royle, Hans Schmid. 2005

315 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/60c5c8c9608ef88ab85c36688f858ee89ad342eb

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Citations in the corpus

Intrinsic heterogeneity in detection probability and its effect on N‐mixture models (2016, background): “& Linkie, M. (2012) Models for species-detection data collected along transects in the presence of abundance-induced heterogeneity and clustering in the detection process. Methods in Ecology and Evolution, 3, 358–367. He, F. & Gaston, K.J. (2000) Estimating species abundance from occurrence.”
unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance (2011, methodology): “First, load Mallard (Anas platyrhynchos) point count dataset described in Kéry et al. (2005).”
Environmental predictors of species richness in forest landscapes: abiotic factors versus vegetation structure (2016, unknown): “Breeding birds were sampled by the Swiss Ornithological Institute following the procedure of the Common Breeding Bird Survey (MHB, K ery et al. (2005)).”
Declines in common, widespread native birds in a mature temperate forest. (2010, unknown): “Statistical techniques have been developed using repeated counts that explicitly estimate both the abundance and the ability to detect birds and can thus remove the confounding effects of changing bird conspicuousness and variable observer skill (Kery et al., 2005).”
Making Great Leaps Forward: Accounting for Detectability in Herpetological Field Studies (2007, methodology): “—Point count models have been used primarily in ornithological contexts (Kéry et al., 2005; Royle et al., 2005).”
Inferences About Landbird Abundance from Count Data: Recent Advances and Future Directions (2009, methodology): “Royle (2004; see also Kery et al. 2005) then proposed use of a reasonable density (e.g., Poisson or negative binomial, with parameters possibly modeled as functions of covariates) for the distribution of true abundances over the spatial sampling locations as the process component of the model.”
EXPERIMENTAL ANALYSIS OF THE AUDITORY DETECTION PROCESS ON AVIAN POINT COUNTS (2007, methodology): “…sampling (Buckland et al. 2001), multipleobserver methods (Nichols et al. 2000, Alldredge et al. in press a), time-ofdetection methods (Farnsworth et al. 2002, Alldredge et al. in press b), double sampling (Bart and Earnst 2002) and repeated count methods (Royle and Nichols 2003, Kery et al. 2005).”
Analysing and mapping species range dynamics using occupancy models (2013, methodology): “To assess the goodness of fit of the best model, we used a parametric bootstrapping approach (K ery et al., 2005) based on a chi-square test statistic for the AIC-best model, which yielded a P-value of 0.88, indicating no evidence of lack of fit of our model as a description of our data set.”
Estimating species richness: calibrating a large avian monitoring programme (2005, background): “Because species differ so much with respect to size, colour, behaviour, habitat and density, heterogeneity among species in detectability can be expected a priori and has indeed been found in previous studies (Boulinier et al . 1998a; Diefenbach, Brauning & Mattice 2003; Kery, Royle & Schmid 2005 )”