Responses to potential threats to welfare vary greatly between species. Even closely related animals often differ in their fear of humans and/or novelty; their behavioural responses to pain; and when captive, their overall welfare and the form and frequency of their stereotypies. Such species differences stimulate hypotheses about I) the way that responses to challenge co-vary with other biological traits; 2) the adaptive value of particular responses; and 3) the factors predicting responses to evolutionarily new scenarios, such as captivity. We illustrate how these ideas can be statistically tested with multi-species comparisons, and show how techniques such as the Comparative Analysis of Independent Contrasts can be used to control for any non-independence of data points caused by species’ relatedness. For each of the three types of hypothesis, we then provide several welfare-relevant examples including one that has been fully tested (respectively, the relationships between sociality and anti-predator behaviour in antelopes; predation pressure, foraging niche and neophobia in parrots; and home range size and stereotypy in carnivores). Ultimate explanations such as these, based on species’ ecology and evolutionary history, have great explanatory appeal. Species comparisons can also have great practical value, allowing the test of hypotheses that would be almost impossible to investigate experimentally, and generating principles that allow predictions about the welfare of similar unstudied species. Multi-species data, for example from the many taxa held in zoos, thus hold enormous potential for increasing the fundamental understanding of animal welfare.

Although horses and donkeys belong to the same genus, their genetic characteristics probably result in specific proteomes and post-translational modifications (PTM) of proteins. Since PTM can alter protein properties, specific PTM may contribute to species-specific characteristics. Therefore, the aim of the present study was to analyse differences in serum protein profiles of horses and donkeys as well as mules, which combine the genetic backgrounds of both species. Additionally, changes in PTM of the protein transthyretin (TTR) were analysed. Serum protein profiles of each species (five animals per species) were determined using strong anion exchanger ProteinChips® (Bio-Rad, Munich, Germany) in combination with surface-enhanced laser desorption ionisation-time of flight MS. The PTM of TTR were analysed subsequently by immunoprecipitation in combination with matrix-assisted laser desorption ionisation-time of flight MS. Protein profiling revealed species-specific differences in the proteome, with some protein peaks present in all three species as well as protein peaks that were unique for donkeys and mules, horses and mules or for horses alone. The molecular weight of TTR of horses and donkeys differed by 30 Da, and both species revealed several modified forms of TTR besides the native form. The mass spectra of mules represented a merging of TTR spectra of horses and donkeys. In summary, the present study indicated that there are substantial differences in the proteome of horses and donkeys. Additionally, the results probably indicate that the proteome of mules reveal a higher similarity to donkeys than to horses.

Recent decades have seen a number of influential attacks on the comparative psychology of learning and intelligence. Two specific charges have been that the use of distantly related species has prevented us from making valid evolutionary inferences and that learning mechanisms are species-specific adaptations to ecological niches and hence not properly comparable between species. It is argued here that work using distantly related species may yield valuable insights into the structure of intelligence and that the question of whether or not learning mechanisms are niche-specific is one which can only be answered by comparative work in “nonnatural” situations. The problems involved in defining and assessing intelligence are discussed. Experimental work has not succeeded in demonstrating differences in intellect among nonhuman vertebrates. Hence the null hypothesis – that there are no differences in intellect among nonhuman vertebrates – should be adopted; the superiority of human intelligence stems from our possessing a species-specific language-acquisition device. One implication of the null hypothesis is that general problem-solving capacity is independent of niche-specific adaptations. A second implication is that problem-solving may involve relatively simple mechanisms; association formation in particular may play a central role in nonhuman intelligence, allowing the successful detection of causal links between events. Causality is a constraint common to all ecological niches.

The present study describes the patterns of NADPH-diaphorase reactivity in the ventral and dorsal lateral geniculate nuclei of rats. In the ventral lateral geniculate nucleus, two distinct populations of NADPH-diaphorase reactive cells are apparent. One population is deeply stained, generally larger in somal size and located in the more superficial or dorsolateral regions of the nucleus. The second population of reactive cells in the nucleus is lightly labeled, small in somal size, and found in deeper or more ventromedial regions of the nucleus. Double labeling with an antibody to GAB A revealed that neither cell class is GABAergic.

In the dorsal lateral geniculate nucleus, reactivity is apparent in lightly labeled small cells only, most of which are GABA immunoreactive also. The NADPH-diaphorase reactive cells, however, form only a small proportion of the total population of GABAergic cells in the nucleus. The striking feature of the NADPH-diaphorase reactive cells in the dorsal lateral geniculate nucleus is their spatial distribution. Most cells are located in the more superficial or dorsolateral areas: very few are apparent in deeper or more ventromedial areas of the nucleus. This distribution closely parallels the location of the outer “shell” region of the nucleus (see Reese, 1988), which receives most of its afferents from the smaller class II and III ganglion cells of the retina and from the superior colliculus.