MODELING ABUNDANCE EFFECTS IN DISTANCE SAMPLING

By J. Andrew Royle, D. Dawson, S. Bates. 2004

319 citations recorded by the source corpus.

Subfields: Ecology, Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/0752843b50f91a2a501c828b18db98ed31d76b1e

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Marc Kéry
2. J. Andrew Royle
3. G. Guillera‐Arroita
4. R. Chandler
5. James D. Nichols
6. L. Thomas
7. Ian J. Fiske
8. B. R. Schmidt

In Statistics and Probability

1. Marc Kéry
2. James D. Nichols
3. R. Chandler
4. J. Andrew Royle
5. L. Thomas
6. C. Amundson
7. C. Handel
8. Ian J. Fiske

Citations in the corpus

• A hierarchical model combining distance sampling and time removal to estimate detection probability during avian point counts (2014, methodology): “Royle et al. (2004) developed a hierarchical distancesampling model for spatially replicated counts with a distance-sampling protocol to estimate and model abundance adjusted for pd (also see Hedley and Buckland 2004, Johnson et al. 2010, Sillett et al. 2012, Oedekoven et al. 2013, Schmidt and…”
• unmarked: An R Package for Fitting Hierarchical Models of Wildlife Occurrence and Abundance (2011, methodology): “The Ni variables are latent and so analysis is carried out based on the integrated likelihood obtained by marginalizing each Ni from the conditional likelihood (Royle et al. 2004):”
• Spatial models for distance sampling data: recent developments and future directions (2013, background): “Perhaps the first such example was Royle et al. (2004), who considered an integrated likelihood model for point and line transects.”
• Species Distribution Models: Ecological Explanation and Prediction Across Space and Time (2009, unknown): “Alternatively, specialized modeling techniques have been developed to account for imperfect detection (e.g., MacKenzie et al. 2002, Royle et al. 2004).”
• Non-recovery of two spotted and spinner dolphin populations in the eastern tropical Pacific Ocean (2005, methodology): “While they are widely used and generally robust, these methods have limitations (Ramsey & Harrison 2004), and modeling the effects is an improved approach (Marques & Buckland 2003, Forcada et al. 2004, Royle et al. 2004).”
• Modelling occurrence and abundance of species when detection is imperfect (2005, methodology): “Royle (2004a) ela- borated on an extension of this approach to modeling abundance from counts that are assumed to have a binomial sampling distribution.”