Animal welfare scientists actively seek reliable and practical metrics that can serve as indicators of animal welfare for use with agricultural, laboratory and zoo-housed animals. Behavioural diversity as a welfare concept originated from early welfare scientists linking poor animal welfare with a high proportion of time spent engaged in stereotyped behaviours and little expression of behaviours that would be expected under wild, or natural conditions. Recently, the concept of behavioural diversity as a welfare indicator has been widely adopted and is frequently quantified by the Shannon-Wiener Diversity Index (H-index). However, the H-Index is fraught with theoretical and mathematical limitations when applied to animal welfare. Four key problems with this metric are demonstrated: the metric's responsivity to the size of the behavioural repertoire and the underlying assumption that larger behavioural repertoires reflect better welfare, the sensitivity of the metric to arbitrary decisions about the resolution of behavioural categories, the fact that the calculation of the metric is agnostic to the valence of behaviours, and the metric's susceptibility to the common practice of excluding some behavioural categories. Moving forward, we recommend focusing on validated welfare measures that are sensitive to valence when evaluating animal welfare.

Results are reported of what is believed to be the first survey of the quantitative contributions Earth scientists make to their research publications. Based on a return of 26 (from 45; 254 total documents), two key patterns are observed. For most articles, there is a steady decrease in the roles of the first through fifth authors. The former fall from 65 ± 14% for two-author outputs, to 52 ± 9% for five, to 46 ± 10% for ten; fifth authors are perceived as having contributed 5–6%. The term ‘balanced’ is used to describe such contributor lists. The second pattern, which is labelled ‘imbalanced’, is recognized with teams of five or more and involves the first author shouldering a disproportionately large amount of the work; consequently, the inputs of the third and lesser authors range from small to negligible (5–1%). In some cases, it is observed in a few of a researcher’s publications (≤3); in others, it is more pervasive. There are two basic explanations: estimation problems and excessive numbers of authors, which can be split into two and three subcategories, respectively. The key features of the survey data are dwelt upon. The work concludes with an exploration of a proposed H-Index-type metric that is weighted by the contribution fractions a researcher makes to their publications. This, I contend, would be more reflective of their impact.