AUTHOR=Ott Swidbert R. 

TITLE=Regressions Fit for Purpose: Models of Locust Phase State Must Not Conflate Morphology With Behavior

JOURNAL=Frontiers in Behavioral Neuroscience

VOLUME=Volume 12 - 2018

YEAR=2018

URL=https://www.frontiersin.org/journals/behavioral-neuroscience/articles/10.3389/fnbeh.2018.00137

DOI=10.3389/fnbeh.2018.00137

ISSN=1662-5153

ABSTRACT=Phenotypic plasticity often entails coordinated changes in multiple traits. The effects of two alternative environments on multiple phenotypic traits can be analysed by multivariable binary logistic regression (LR). Locusts are grasshopper species (family Acrididae) with a capacity to transform between two distinct integrated phenotypes or 'phases' in response to changes in population density: a solitarious phase, which occurs when densities are low, and a gregarious phase, which arises as a consequence of crowding and can form very large and economically damaging swarms. The two phases differ in behaviour, physiology and morphology. A large body of work on the mechanistic basis of behavioural phase transitions has relied on LR models to estimate the probability of behavioural gregariousness from multiple behavioural variables. Martín-Blázquez and Bakkali (2017, Entomologia Experimentalis et Applicata 163, 9–25) have recently proposed standardised LR models for estimating an overall 'gregariousness level' from a combination of behavioural and, unusually, morphometric variables. Here I develop a detailed argument to demonstrate that the premise of such an overall 'gregariousness level' is fundamentally flawed, since locust phase transformations entail a decoupling of behaviour and morphology. LR models that combine phenotypic traits with markedly different response times to environmental change are of very limited value for analyses of phase change in locusts, and of environmentally induced phenotypic transitions in general. I furthermore show why behavioural variables should not be adjusted by measures of body size that themselves differ between the two phases. I discuss the models fitted by Martín-Blázquez and Bakkali (2017) to highlight potential pitfalls in statistical methodology that must be avoided when analysing associations between complex phenotypes and alternative environments. Finally, I reject the idea that 'standardised models' provide a valid shortcut to estimating phase state across different developmental stages, strains or species. The points addressed here are pertinent to any research on transitions between complex phenotypes and behavioural syndromes.