Evaluation of some random effects methodology applicable to bird ringing data

By K. Burnham, G. White. 2002

199 citations recorded by the source corpus.

Subfields: Ecology, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/3074c7806aa1e679a29371de2a706ac61a31de7f

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In Ecology

In Nature and Landscape Conservation

Citations in the corpus

Modelling demography and extinction risk in the endangered Balearic shearwater (2004, methodology): “…partitioned the variance of the apparent survival rates into sampling variance and process variance using random effects models, since a large sampling variance makes difficult the identification of the biological processes underlying the variability in survival (e.g. Burnham and White, 2002).”
Model Selection in Linear Mixed Models (2013, unknown): “Burnham and White (2002) and Burnham and Anderson (2002) propose using the function αn,BW (θ̂) = 2{ρ(τ̂ ) + q}.”
Variation and covariation in survival, dispersal, and population size in barn owls Tyto alba (2003, methodology): “Ecological Society, Journal of Animal Ecology, 72, 391‐399 reflects imprecise estimation of the random effects method as a result of the short time series, which may be at the lower limit for applying this method ( Burnham & White 2002 ).”
Variation of primary production during winter induces synchrony in survival rates in migratory white storks Ciconia ciconia (2005, methodology): “This method allows the separation of sampling variance from process variance ( Burnham & White 2002 ).”
Chapter 3 Modeling Individual Animal Histories with Multistate Capture–Recapture Models (2009, background): “Capture–reencounter models with random effects present specific technical difficulties, in particular computational ones (Brooks et al., 2000, 2002; Burnham and White, 2002).”
WinBUGS for population ecologists: bayesian modeling using markov chain Monte Carlo methods (2009, methodology): “…that could be handled by using approximations (Chavez-Demoulin 1999), circumvented by resorting to asymptotic arguments (Gould and Nichols 1998; Burnham and White 2002), or numerical integration (e.g. importance sampling: Skaug and Fournier 2006 or Gaussian quadrature: Wintrebert et al. 2005).”
SPATIAL AND TEMPORAL VARIATION IN DETECTION PROBABILITY OF PLETHODON SALAMANDERS USING THE ROBUST CAPTURE–RECAPTURE DESIGN (2004, background): “Incorporating “random effects” into capture–recapture models is an active field of research (Burnham and White 2002, Burnham and Anderson 2002, Schwarz 2002), and better approaches likely will be developed.”
Fire frequency matters more than fire size: Testing the pyrodiversity-biodiversity paradigm for at-risk small mammals in an Australian tropical savanna (2015, methodology): “Therefore, we used variance components to estimate both model parameters and environmental (or process) variation for both multi-state (survival and state transition) and recruitment models (Burnham et al., 1987; Burnham and White, 2002).”
Application of random effects to the study of resource selection by animals. (2006, methodology): “Natarajan & McCulloch 1999; Burnham & White 2002; Krawchuk & Taylor 2003).”