Foraging mode and locomotor capacities in Lacertidae

Verwaijen, D.; Damme, Raoul Van

doi:10.1163/156853808784124965

Cited by 10 publications

(2 citation statements)

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“…The causes of correlation in telemetry studies are varied and may be linked to physical and physiological limitations (e.g. constraints on the speed of the animal; Fancy & White 1987;Verwaijen & Van Damme 2008), within animal behavioural processes (e.g. periodic feeding patterns or migration schedules; Cushman et al 2005;Fryxell et al 2008), between animal behavioural processes (e.g.…”

Section: Introductionmentioning

confidence: 99%

Correlation and studies of habitat selection: problem, red herring or opportunity?

Fieberg

Matthiopoulos

Hebblewhite

et al. 2010

Phil. Trans. R. Soc. B

247

288

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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.

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Section: Introductionmentioning

confidence: 99%

Correlation and studies of habitat selection: problem, red herring or opportunity?

Fieberg

Matthiopoulos

Hebblewhite

et al. 2010

Phil. Trans. R. Soc. B

247

288

View full text Add to dashboard Cite

show abstract

“…Researchers have used MPM to compare foraging behaviour across species (Reilly et al, 2007), explore questions regarding the foraging mode controversy (i.e. whether foraging behaviour has two discrete modes -Butler, 2005;Cooper, 2005b), and search for association between foraging behaviour and other variables, such as morphology (Botero-Delgadillo & Bayly, 2012), physiology and performance (Miles, Losos, & Irschick, 2007;Verwaijen & Van Damme, 2008b), colouration Hawlena, 2009;Hawlena, Boochnik, Abramsky, & Bouskila, 2006), and environmental conditions (Verwaijen & Van Damme, 2008a). Yet, the simplicity of MPM that makes it so popular also harbours intrinsic methodological problems that thus far have passed largely unnoticed.…”

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confidence: 99%

How to use (and not to use) movement‐based indices for quantifying foraging behaviour

2017

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Movement‐based indices such as moves per minute (MPM) and proportion time moving (PTM) are common methodologies to quantify foraging behaviour. We explore fundamental drawbacks of these indices that question the ways scientists have been using them and propose new solutions.To do so, we combined analytical and simulation models with lizards foraging data at the individual and species levels.We found that the maximal value of MPM is constrained by the minimal durations of moves and stops. As a result, foragers that rarely move and those that rarely stop are bounded to similar low MPM values. This implies that (1) MPM has very little meaning when used alone, (2) MPM and PTM are interdependent, and (3) certain areas in the MPM‐PTM plane cannot be occupied. We also found that MPM suffers from inaccuracy and imprecision.We introduced a new bias correction formula for already published MPM data, and a novel index of changes per minute (CPM) that uses the frequency of changes between move and stop bouts. CPM is very similar to MPM, but does not suffer from bias. Finally, we suggested a new foraging plane of average move and average stop durations. We hope that our guidelines of how to use (and not to use) movement‐based indices will add rigor to the study of animals’ foraging behaviour.

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Instantaneous Versus Interval Speed Estimates of Maximum Locomotor Capacities for Whole-Organism Performance Studies

2017

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Foraging mode and locomotor capacities in Lacertidae

Cited by 10 publications

References 50 publications

Correlation and studies of habitat selection: problem, red herring or opportunity?

Correlation and studies of habitat selection: problem, red herring or opportunity?

How to use (and not to use) movement‐based indices for quantifying foraging behaviour

Instantaneous Versus Interval Speed Estimates of Maximum Locomotor Capacities for Whole-Organism Performance Studies

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