Abstract: The present paper focuses on six main issues. First, we briefly explain why an increased understanding of the human-animal relationship (HAR) is an essential component of any strategy intended to improve the welfare of farmed animals and their stockpersons. Second, we list the main internal and external factors that can influence the nature of the relationship and the interactions between human beings and farm animals. Third, we argue that the numerous tests that have been used to assess the HAR fall into three main categories (stationary human, moving human, handling/restraint), according to the degree of human involvement. Fourth, the requirements that any test of HAR must fulfil before it can be considered effective, and the ways in which the tests can be validated are discussed. Fifth, the various types of test procedures that have been used to assess the HAR in a range of farmed species are reviewed and critically discussed. Finally, some research perspectives that merit further attention are shown. The present review embraces a range of farmed animals. Our primary reasons for including a particular species were: whether or not general interest has been expressed in its welfare and its relationship with humans, whether relevant literature was available, and whether it is farmed in at least some European countries. Therefore, we include large and small ruminants (cattle, sheep, goats), pigs, poultry (chickens), fur animals (foxes, mink) and horses. Although horses are primarily used for sport, leisure or therapy they are farmed as draught, food or breeding animals in many countries. Literature on the HAR in other species was relatively scarce so they receive no further mention here.

Abstract: Single behavioural differences between egalitarian and despotic animal societies are often assumed to reflect specific adaptations. However, in the present paper, I will show in an individual-orientated model, how many behavioural traits of egalitarian and despotic virtual societies arise as emergent characteristics. The artificial entities live in a homogeneous world and only aggregate, and upon meeting one another and may perform dominance interactions in which the effects of winning and losing are self-reinforcing. The behaviour of these entities is studied in a similar way to that of real animals. It will be shown that by varying the intensity of aggression only, one may switch from egalitarian to despotic virtual societies. Differences between the two types of society appear to correspond closely to those between despotic and egalitarian macaque species in the real world. In addition, artificial despotic societies show a clearer spatial centrality of dominants and, counter-intuitively, more rank overlap between the sexes than the egalitarian ones. Because of the correspondence with patterns in real animals, the model makes it worthwhile comparing despotic and egalitarian species for socio-spatial structure and rank overlap too. Furthermore, it presents us with parsimonious hypotheses which can be tested in real animals for patterns of aggression, spatial structure and the distribution of social positive and sexual behaviour.

Abstract: The evaluation of important parameters for measuring the horses’ cognitive capacities is one of the central topics of the equine behaviour team at Nürtingen-Geislingen University. Social complexity has been said to be one of the settings in which needs for cognitive capacities arise in animals. A variety of studies throughout the last two decades proved the horses’ social complexity to be far more elaborate than previously assumed. Horses form social bonds for the protection of offspring, intervene in encounters of others, identify group mates individually and easily orientate in a fission fusion society.
In such socially complex societies, animals will benefit from learning socially. In many bird and primate species the degree of social complexity correlates nicely with the species abilities for social learning. Social learning was, therefore, argued to be an indicator for elaborate mental capacities in animals. We were delighted to prove that horses actually copy social behaviour and techniques for operating a feeding apparatus from older and higher ranking group members. In a recent study we found young horses, at the age of 3 to 12, to copy the operation of a feeding apparatus from a human demonstrator. Social learning seems to work nicely in horses when the social background of the animals is considered.
The degree to which individual animals adapt to changes in their social or physical environment by finding innovative solution appears to be the other side of the coin, of whether animals adjust to challenges by social learning. It is not very astonishing, that along with the animals’ social complexity and their ability to learn socially also the degree to which they show innovative behaviour was claimed to be one of the most important demonstrations of advanced cognitive capacities. In a recent approach, we started to ask horse owners and horse keepers in many countries to tell us about unusual behaviour of their horses via a web site (http://innovative-behaviour.org). To date, we received 204 cases of innovative behaviour descriptions from which six cases were clear examples of tool use or borderline tool use. We categorized the innovative behaviours into the classes, a) innovations to gain food, b) innovations to gain freedom, c) social innovations, d) innovations to increase maintenance, and e) innovations that could not be clearly assigned to a category. About 20% of the innovative horses showed more than one innovation. These animals could be termed “true innovators”. Again, young horses were more innovative than older ones with the age group 5 – 9 showing the highest number of innovative behaviour descriptions.
In a nutshell, the horses’ cognitive capacities appear to be underestimated throughout the last decades. The horses’ social complexity is far more elaborate than previously assumed, horses learn socially from conspecific and humans, some of them demonstrate innovative behaviour adaptations to their environment and even simple forms of tool use.

Abstract: The bedding preferences of ponies were determined using video recordings of nighttime (1900 to 0700) behavior of individually housed ponies. The ponies' behavior each minute was recorded to determine time budgets. In Exp. I, preference for bedding was determined using three mares, three stallions and two geldings given access to bedded and unbedded areas in a box stall. The ponies spent more time (66%) on the bedded area and were never observed lying on the unbedded areas. In Exp. II, three mares and six stallions were given access to a box stall, one side of which was bedded with wood shavings and the other with straw. Although some individual animals preferred one bedding over the other, neither form of bedding was preferred consistently. Time budgets in Exp. II were similar on both bedding materials. The ponies spent 12% of their nighttime lying, 2% walking, 35% eating and 50% standing inactively. Some ponies had a relatively strong preference for bedding, but the type of bedding preferred varied with the individual animal. Some individual ponies had no clear preference, but instead had a side or position preference

Abstract: Blood was collected every 3 days for 13 months from 4 captured [female][female] of proven fertility kept adjacent to a teaser stallion. Basal plasma LH level was greater during Apr.-July (8.1+or-0.5 ng/ml) than during Nov.-Jan. (2.2+or-0.2). A total for 21 LH peaks occurred between 13 Apr. and 31 Aug. among the 4 [female][female]; many peaks exceeded 20 times the basal level, and there was a trend to a higher LH level with each succeeding peak. On all occasions except one, LH peaks were associated with progesterone levels of 0.5 ng/ml and with increases of oestrogen (peak average 43.1+or-12.1 pg/ml). Basal progesterone level during Apr.-July (1.5+or-1.2 ng/ml) did not differ significantly from that during Oct.-Jan. (1.1+or-0.7), nor did basal oestrogen level differ significantly between those 2 periods (8.4+or-3.2 and 12.9+or-4.6 pg/ml resp.). Behavioural oestrus always occurred with LH and oestrogen peaks during Apr.-July. However, behavioural oestrus was occasionally observed during Aug.-Oct., when LH peaks no longer occurred.