ABSTRACT
‘Animal personality’ is considered formed through complex interactions of an individual and its surrounding environment. How can we quantify the ‘personality’ of an individual? Although there is no clear consensus, quantifying intra- and inter-individual variations of behavior, or individual behavioral type, is a prerequisite in the studies of animal personality. We propose a statistical method to measure the appropriateness of our assumption of ‘individual’ in repeatedly measured behavioral data, from each individual from a predictive point of view. For a model case, we studied the sponge crab Lauridromia dehaani known to make a ‘cap’ from a natural sponge and carry it for camouflage. Because a cap is most likely to be rebuilt and replaced repeatedly, we hypothesized that each individual crab would grow a unique behavioral type and it would be observed under an experimentally controlled environmental condition. To test the hypothesis, we conducted behavioral experiments and newly took an approach of Bayesian model comparison to examine whether the crab has the individual behavioral type in the cap making behavior. The behavioral choices were given to a crab using artificial sponges of three different sizes. We did statistical modeling to implement hierarchical structure specifying the behavioral type. We modeled a choice of sponges, size of a trimmed part of a cap, size of a cavity of a cap, latency to produce a cap, as random variables in 26 models. In addition, we calculated widely applicable information criterion (WAIC) value for each model to evaluate the models from the predictive point of view. As a result, the crabs less than about 9 cm were found to make caps from the sponges. The body size well explained the behavioral variables, choice, trimmed and cavity size, but not the latency. The behavioral type was captured as a difference of WAIC of the models. Thus, we captured the behavioral type as a probabilistic distribution structure in the behavioral data. Our statistical approach is not limited to behavioral data but also applicable to physiological or morphological data when one would try to examine if some group structure would exist behind fluctuating empirical data.
Footnotes
major revision in texts, figures; definition of WAIC for hierarchical models described;