Lamb survival is known to be a key component of reproductive efficiency in sheep flocks. It has been the subject of a large number of studies over the decades and this review provides an update and insights into the latest understanding of the extent and variability of lamb losses across Australia. The pattern of causes of lamb losses, including dystocia, starvation/exposure, mismothering and predation, are examined. Likewise the importance of birthweight in contributing to such losses is discussed as are strategies for improving lamb survival. The strategies examined include improved ewe nutrition, shelter provision and selection for cold resistance and improved maternal behaviour.

Genetic parameters for carcass and meat quality traits of about 18-month-old Merino rams (n = 5870), the progeny of 543 sires from three research resource flocks, were estimated. The estimates of heritability for hot carcass weight (HCW) and the various fat and muscle dimension measurements were moderate and ranged from 0.20 to 0.37. The brightness of meat (colour L*, 0.18 +/- 0.03 standard error) and meat pH (0.22 +/- 0.03) also had moderate estimates of heritability, although meat relative redness (colour a*, 0.10 +/- 0.03) and relative yellowness (colour b*, 0.10 +/- 0.03) were lower. Heritability estimates for live weights were moderate and ranged from 0.29 to 0.41 with significant permanent maternal environmental effects (0.13 to 0.10). The heritability estimates for the hogget wool traits were moderate to high and ranged from 0.27 to 0.60. The ultrasound measurements of fat depth (FATUS) and eye muscle depth (EMDUS) on live animals were highly genetically correlated with the corresponding carcass measurements (0.69 +/- 0.09 FATC and 0.77 +/- 0.07 EMD). Carcass tissue depth (FATGR) had moderate to low genetic correlations with carcass muscle measurements [0.18 +/- 0.10 EMD and 0.05 +/- 0.10 eye muscle area (EMA)], while those with FATC were negative. The genetic correlation between EMD and eye muscle width (EMW) was 0.41 +/- 0.08, while EMA was highly correlated with EMD (0.89 +/- 0.0) and EMW (0.78 +/- 0.04). The genetic correlations for muscle colour with muscle measurements were moderately negative, while those with fat measurements were close to zero. Meat pH was positively correlated with muscle measurements (0.14 to 0.17) and negatively correlated with fat measurements (-0.06 to -0.18). EMDUS also showed a similar pattern of correlations to EMD with meat quality indicator traits, although FATUS had positive correlations with these traits which were generally smaller than their standard error. The genetic correlations among the meat colour traits were high and positive while those with meat pH were high and negative, which were all in the favourable direction. Generally, phenotypic correlations were similar or slightly lower than the corresponding genetic correlations. There were generally small to moderate negative genetic correlations between clean fleece weight (CFW) and carcass fat traits while those with muscle traits were close to zero. As the Merino is already a relatively lean breed, this implies that particular attention should be given to this relationship in Merino breeding programmes to prevent the reduction of fat reserves as a correlated response to selection for increased fleece weight. The ultrasound scan traits generally showed a similar pattern to the corresponding carcass fat and muscle traits. There was a small unfavourable genetic correlation between CFW and meat pH (0.19 +/- 0.07).

The objective of the present study was to examine the factors associated with the death of neonatal lambs. Postmortem autopsy data were collected from 3198 newborn lambs in the Sheep CRCs Information Nucleus Flock situated in various environments throughout southern Australia. The proportion dying by category from highest to lowest was starvation–mismothering (25%), stillbirth (21%), birth injury (18%), dystocia (9%), death in utero–prematurity (10%), predation (7%), cold exposure (5%), undiagnosed (4%), infection (1%) or misadventure (1%). Factors best explaining the probability of lambs falling into a death category included both birth type and birthweight for dystocia, stillbirth, starvation–mismothering and death in utero–prematurity. The probability of a lamb falling into any category was predicted at the mean birthweight, within birth type. Single-born lambs were more likely to die from dystocia and stillbirth, while twin lambs were more likely to die from birth injury, starvation–mismothering or from undiagnosed causes. Triplet lambs were more likely to die from starvation–mismothering or death in utero–prematurity. Sire type (Merino, maternal or terminal) did not affect the proportions of lambs within any category. The proportions lost to each cause of death were largely consistent among locations, despite the rate of death varying. Dystocia, stillbirth and birth injury, as evidenced by the presence of oedema around the head and neck or by lesions of the central nervous system, accounted for 48% of autopsied lambs. We conclude that for improvements to occur in the rates of lamb survival, the Australian sheep industry must focus on minimising losses due to dystocia, stillbirth, birth injury and starvation.