Abstract: Coat clipping is a common practice in sport horses; however, timing, purpose, technique, and clips vary widely, as do the management and feeding of a clipped horse. The aim of this study was to collect data regarding common clipping practices. A questionnaire was published online in Germany and contained 32 questions. Four hundred ninety-eight people answered at least one question, and 373 individuals (7% male, 93% female; ages 14–59 years) completed all the questions. Clipped horses were predominantly used as sport horses (68%), and they were either clipped immediately before or during the winter season (88%) or year-round (7%). The clipping date was scheduled according to hair length (52%), sweat amount (47%), and drying time (47%). Participants primarily used two clips: the hunter clip and the blanket clip, both without clipping the head (23% each). The majority of the clipped horses wore a blanket day and night (> 90%). Future studies with observations in the field are needed to support survey data in an effort to develop welfare recommendations for clipping practices utilized with horses.

Abstract: Assessing the animal welfare state is a challenge given the subjective individual cognitive and emotional processing involved. Electroencephalography (EEG) spectrum analysis has proved an ecologically valid recording situation to assess the link between brain processes and affective or cognitive states in humans: a higher slow wave/fast wave ratio has been associated with a positive internal state. In particular, a high production of theta power (3-8 Hz) has been related to positive emotions. On the other hand, it has been hypothesized that a left hemisphere (LH) dominance may be associated with a better welfare state. Here, we test the hypothesis that individual differences in the resting-state quantitative EEG power spectrum of adult horses (N = 18) and its lateralization pattern may reflect individual subjective perception of their conditions of life and welfare state. The results show clear individual differences in the proportions of the different waves and their inter-hemispheric distribution. Three different EEG power spectrum profiles were highlighted, from a bilateral predominance of theta waves in horses in a more positive welfare state to a bilateral predominance of beta waves in horses with clear expressions of compromised welfare. Interestingly, particular correlations were found between wave power activity and welfare parameters. We found a negative correlation between the number of stereotypic behaviours per hour and the median proportion of theta waves in the left hemisphere. and between the overall state (total chronic stress score) of welfare and gamma production in the right hemisphere (RH). These findings go along the hypothesis of a particular involvement of the left hemisphere for positive processing and of the right hemisphere for negative processing. However, the pattern of laterality did not appear as the most important feature here as both extreme clusters in terms of welfare showed bilateral predominance of one wave type. It is possible that hemispheric specialization makes more sense during acute emotion-inducing conditions rather than in this resting-state context (i.e. in absence of any high emotion-inducing stimulation), although the opposition gamma versus theta waves between both hemispheres in the horses with an intermediate welfare state is noticeable and intriguing. It seems that bilateral but also LH theta activity is a promising neurophysiological marker of good welfare in horses, while a bilateral or RH high production of gamma waves should alert about potential welfare alterations. Quantitative resting-state EEG power spectrum appears as a highly promising tool for exploring the brain processes involved in the subjective perception of chronic welfare, as a useful complementary tool for welfare assessment.

Abstract: Summary Many publications documenting large-scale trends in the distribution of species make use of opportunistic citizen data, that is, observations of species collected without standardized field protocol and without explicit sampling design. It is a challenge to achieve reliable estimates of distribution trends from them, because opportunistic citizen science data may suffer from changes in field efforts over time (observation bias), from incomplete and selective recording by observers (reporting bias) and from geographical bias. These, in addition to detection bias, may lead to spurious trends. We investigated whether occupancy models can correct for the observation, reporting and detection biases in opportunistic data. Occupancy models use detection/nondetection data and yield estimates of the percentage of occupied sites (occupancy) per year. These models take the imperfect detection of species into account. By correcting for detection bias, they may simultaneously correct for observation and reporting bias as well. We compared trends in occupancy (or distribution) of butterfly and dragonfly species derived from opportunistic data with those derived from standardized monitoring data. All data came from the same grid squares and years, in order to avoid any geographical bias in this comparison. Distribution trends in opportunistic and monitoring data were well-matched. Strong trends observed in monitoring data were rarely missed in opportunistic data. Synthesis and applications. Opportunistic data can be used for monitoring purposes if occupancy models are used for analysis. Occupancy models are able to control for the common biases encountered with opportunistic data, enabling species trends to be monitored for species groups and regions where it is not feasible to collect standardized data on a large scale. Opportunistic data may thus become an important source of information to track distribution trends in many groups of species.

Abstract: Abstract When living in a group, individuals have to make trade-offs, and compromise, in order to balance the advantages and disadvantages of group life. Strategies that enable individuals to achieve this typically affect inter-individual interactions resulting in nonrandom associations. Studying the patterns of this assortativity using social network analyses can allow us to explore how individual behavior influences what happens at the group, or population level. Understanding the consequences of these interactions at multiple scales may allow us to better understand the fitness implications for individuals. Social network analyses offer the tools to achieve this. This special issue aims to highlight the benefits of social network analysis for the study of primate behaviour, assessing it's suitability for analyzing individual social characteristics as well as group/population patterns. In this introduction to the special issue, we first introduce social network theory, then demonstrate with examples how social networks can influence individual and collective behaviors, and finally conclude with some outstanding questions for future primatological research. Am. J. Primatol. 73:703?719, 2011. ? 2011 Wiley-Liss, Inc.