TY - JOUR
T1 - Correlation and studies of habitat selection
T2 - Problem, red herring or opportunity?
AU - Fieberg, John
AU - Matthiopoulos, Jason
AU - Hebblewhite, Mark
AU - Boyce, Mark S.
AU - Frair, Jacqueline L.
PY - 2010/7/27
Y1 - 2010/7/27
N2 - With the advent of new technologies, animal locations are being collected at ever finer spatiotemporal scales. We review analytical methods for dealing with correlated data in the context of resource selection, including post hoc variance inflation techniques, 'two-stage' approaches based on models fit to each individual, generalized estimating equations and hierarchical mixed-effects models. These methods are applicable to a wide range of correlated data problems, but can be difficult to apply and remain especially challenging for use-availability sampling designs because the correlation structure for combinations of used and available points are not likely to follow common parametric forms. We also review emerging approaches to studying habitat selection that use finescale temporal data to arrive at biologically based definitions of available habitat, while naturally accounting for autocorrelation by modelling animal movement between telemetry locations. Sophisticated analyses that explicitly model correlation rather than consider it a nuisance, like mixed effects and state-space models, offer potentially novel insights into the process of resource selection, but additional work is needed to make them more generally applicable to large datasets based on the use-availability designs. Until then, variance inflation techniques and two-stage approaches should offer pragmatic and flexible approaches to modelling correlated data.
AB - With the advent of new technologies, animal locations are being collected at ever finer spatiotemporal scales. We review analytical methods for dealing with correlated data in the context of resource selection, including post hoc variance inflation techniques, 'two-stage' approaches based on models fit to each individual, generalized estimating equations and hierarchical mixed-effects models. These methods are applicable to a wide range of correlated data problems, but can be difficult to apply and remain especially challenging for use-availability sampling designs because the correlation structure for combinations of used and available points are not likely to follow common parametric forms. We also review emerging approaches to studying habitat selection that use finescale temporal data to arrive at biologically based definitions of available habitat, while naturally accounting for autocorrelation by modelling animal movement between telemetry locations. Sophisticated analyses that explicitly model correlation rather than consider it a nuisance, like mixed effects and state-space models, offer potentially novel insights into the process of resource selection, but additional work is needed to make them more generally applicable to large datasets based on the use-availability designs. Until then, variance inflation techniques and two-stage approaches should offer pragmatic and flexible approaches to modelling correlated data.
KW - Generalized estimating equation
KW - Generalized linear mixed model
KW - Hierarchical model
KW - Resource-selection function
KW - Telemetry
KW - Use-availability
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U2 - 10.1098/rstb.2010.0079
DO - 10.1098/rstb.2010.0079
M3 - Review article
C2 - 20566500
AN - SCOPUS:77955185926
SN - 0962-8436
VL - 365
SP - 2233
EP - 2244
JO - Philosophical Transactions of the Royal Society B: Biological Sciences
JF - Philosophical Transactions of the Royal Society B: Biological Sciences
IS - 1550
ER -