Reporting and interpreting non-significant results in animal cognition research.

How statistically non-significant results are reported and interpreted following null hypothesis significance testing is often criticized. This issue is important for animal cognition research because studies in the field are often underpowered to detect theoretically meaningful effect sizes, i.e., often produce non-significant p-values even when the null hypothesis is incorrect. Thus, we manually extracted and classified how researchers report and interpret non-significant p-values and examined the p-value distribution of these non-significant results across published articles in animal cognition and related fields. We found a large amount of heterogeneity in how researchers report statistically non-significant p-values in the result sections of articles, and how they interpret them in the titles and abstracts. Reporting of the non-significant results as "No Effect" was common in the titles (84%), abstracts (64%), and results sections (41%) of papers, whereas reporting of the results as "Non-Significant" was less common in the titles (0%) and abstracts (26%), but was present in the results (52%). Discussions of effect sizes were rare (<5% of articles). A p-value distribution analysis was consistent with research being performed with low power of statistical tests to detect effect sizes of interest. These findings suggest that researchers in animal cognition should pay close attention to the evidence used to support claims of absence of effects in the literature, and-in their own work-report statistically non-significant results clearly and formally correct, as well as use more formal methods of assessing evidence against theoretical predictions.

Goffin's cockatoos discriminate objects based on weight alone.

Paying attention to weight is important when deciding upon an object's efficacy or value in various contexts (e.g. tool use, foraging). Proprioceptive discrimination learning, with objects that differ only in weight, has so far been investigated almost exclusively in primate species. Here, we show that while Goffin's cockatoos learn faster when additional colour cues are used, they can also quickly learn to discriminate between objects on the basis of their weight alone. Ultimately, the birds learned to discriminate between visually identical objects on the basis of weight much faster than primates, although methodological differences between tasks should be considered.

The measure of spatial position within groups that best predicts predation risk depends on group movement.

Both empirical and theoretical studies show that an individual's spatial position within a group can impact the risk of being targeted by predators. Spatial positions can be quantified in numerous ways, but there are no direct comparisons of different spatial measures in predicting the risk of being targeted by real predators. Here, we assess these spatial measures in groups of stationary and moving virtual prey being attacked by three-spined sticklebacks (Gasterosteus aculeatus). In stationary groups, the limited domain of danger best predicted the likelihood of attack. In moving groups, the number of near neighbours was the best predictor but only over a limited range of distances within which other prey were counted. Otherwise, measures of proximity to the group's edge outperformed measures of local crowding in moving groups. There was no evidence that predators preferentially attacked the front or back of the moving groups. Domains of danger without any limit, as originally used in the selfish herd model, were also a poor predictor of risk. These findings reveal that the collective properties of prey can influence how spatial position affects predation risk, via effects on predators' targeting. Selection may therefore act differently on prey positioning behaviour depending on group movement.