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Chantier qualité GASea bass is a major species in Mediterranean aquaculture, but has a distribution area ranging from North Atlantic to South Mediterranean, with a population structure previously revealed by population genetics. To test the farming performances of wild sea bass populations, we produced a partial diallel cross mating scheme, using sires originating from North Atlantic (NAT), South Atlantic (SAT), West Mediterranean (WEM), North-East Mediterranean (NEM) and South-East Mediterranean (SEM). Fifteen sires per origin were mated in a full-factorial design using artificial fertilization with 9 NAT dams and 17 WEM dams, producing 10 population crosses and 1950 potential full-sib families. All fish were reared together, then tagged at an average weight of 20 g and distributed to four different sites (1800 fish per site). They were grown to an objective of 200 g mean weight, where 737 to 775 fish were slaughtered in each site, and their parentage was recovered using 6 to 7 microsatellite loci, resulting in 98.9% unique assignments. All populations had similar growth rates until tagging size (20 g), but differences appeared later on. No heterosis appeared for growth rate, and genotype by environment interaction (G × E) at the population level was limited, with a significant re-ranking only in one rearing site, while strong G × E for growth rate was observed within populations. Populations were different in shape, muscular fat content, and carcass yield, but not in fillet yield. In general, heterosis was absent and G × E was very limited between populations. No "ideal" population combining all favorable traits was identified. Differences between extreme populations ranged between 3 and 49% of the mean, depending on the traits. Interestingly, in almost all cases, these differences were within the reach of one generation of intense (5%) phenotypic selection

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DOI: 10.15835/nsb13110859 Livestock farming with sheep represents an important income stream. With climate change, domestic sheep are being exposed to heat stress which can have adverse effects on growth. Here, data regarding sheep behaviour in response to high temperature stress was analysed using the Euclidean distance method to integrate all variables into a single representative outcome that could summarize sheep behaviour. We studied the effects of two shepherding conditions either with or without the provision of shade. The number of animals eating grass, ruminating and resting either in the shade or directly in the sun were recorded over one year at two-week intervals. As the ideal behaviour (expert’s criteria), the following conditions were considered: maximum numbers of animals eating grass, ruminating and resting under shaded conditions were desirable; while the numbers of animals ruminating or resting under direct sunlight should be at a minimum. The statistical evaluation undertaken integrated these variables to identify the most significant effects of heat stress. Sheep spent most of the daylight hours engaged in eating and this activity was more intensive where shaded conditions were available. The Euclidean distance calculated for the group of animals maintained under shaded conditions was statistically lower (indicating better behaviour). Based on this, it is possible to accurately rank the treatments in terms of severity. The analysis indicates that the use of the Euclidean distance could be used to summarize a simplified outcome for observational data collected in behavioural studies in response to differing climatic conditions.

Sheep farming, and the income generated from this endeavor, contributes significantly to the global economy and rural livelihoods. Therefore, it is vital to maintain the productivity of this industry in the face of changing climate patterns. In the context of sheep farming, animals are exposed to a higher heat load as global temperatures are increasing, leading to heat stress. This heat stress conditions can adversely affect animal productivity and welfare resulting in reduced feed intake, physiological (panting, higher respiration, higher heart rate, etc.) and behavioral changes (lying down, standing, seeking shade, etc.) to compensate for increased heat load ultimately leading to lowered productivity. Considering this, it is important to monitor sheep behavior in order to implement improved management practices to compensate for changes in climate. The current short study investigated sheep behavior at different times throughout the day. The data generated was analyzed using the hierarchical cluster analysis method in order to integrate all variables into a single representative dendrogram that could summarize sheep behavior. While hierarchical cluster analysis has been applied in diverse scientific fields, as far as we know, the statistical application reported here is novel in the context of sheep behavior in response to climate change. We studied sheep behavior throughout the day (9:00 – 9:50; 10:00 – 10:50; 11:00 – 11:50; 14:00 – 14:50; 15:00 – 15:50; 16:00 – 16:50). Shade was provided in the form of trees. The following indicators were recorded over a period of twelve months at two week intervals: number of animals eating grass, ruminating and resting. The statistical evaluations undertaken resulted in the generation of a dendrogram which integrated all evaluated variables to categorize the behaviors undertaken at different times during the day. The dendrogram indicated three groupings of sheep behavior that were distinctly different from each other. The analysis shown here indicates that the use of hierarchical cluster analysis culminating in the construction of a dendrogram can effectively synthesize large datasets to outline similar relationships (in this study, this was in the context of observed behaviors). This statistical method applied to sheep physiological studies may help interpret experimental data in the context of climatic change.