We present estimates of the selection on and the heritability of a male secondary sexual weapon in a wild population: antler size in red deer. Male red deer with large antlers had increased lifetime breeding success, both before and after correcting for body size, generating a standardized selection gradient of 0.44 (+/- 0.18 SE). Despite substantial age- and environment-related variation, antler size was also heritable (heritability of antler mass = 0.33 +/- 0.12). However the observed selection did not generate an evolutionary response in antler size over the study period of nearly 30 years, and there was no evidence of a positive genetic correlation between antler size and fitness nor of a positive association between breeding values for antler size and fitness. Our results are consistent with the hypothesis that a heritable trait under directional selection will not evolve if associations between the measured trait and fitness are determined by environmental covariances: In red deer males, for example, both antler size and success in the fights for mates may be heavily dependent on an individual's nutritional state.

Classical population genetics theory predicts that selection should deplete heritable genetic variance for fitness. We show here that, consistent with this prediction, there was a negative correlation between the heritability of a trait and its association with fitness in a wild population of red deer (Cervus elaphus) and there was no evidence of significant heritability of total fitness. However, the decline in heritability was caused, at least in part, by increased levels of residual variance in longevity and, hence, in total fitness: in this population, longevity is known to be heavily influenced by environmental factors. Other life history traits that were not associated with longevity, such as average annual breeding success, had higher heritabilities. Coefficients of additive genetic variance differed markedly between traits, but highly skewed measures, such as male breeding success, generally had greater coefficients of variance than morphometric traits. Finally, there were significant maternal effects in a range of traits, particularly for females.

During the early postpartum period dairy cows mobilize fat and muscle to support lactation. This is associated with alterations in blood metabolite and hormone profiles which in turn influence milk yield and fertility. This study developed models to determine how metabolic traits, milk yield and body condition score were inter-related at different times in the periparturient period and to compare these relationships in primiparous (PP, n=188) and multiparous (MP, n=312) cows. Data from four previous studies which included information on blood metabolic parameters, parity, milk yield, body condition score and diet were collated into a single dataset. Coefficients of polynomial equations were calculated for each trait between -1 week pre-calving and week +7 postpartum using residual maximum likelihood modelling. The completed dataset was used in a multiple correlation model to determine how the best fit curves were related to each other over time. PP cows had higher concentrations of insulin-like growth factor-I and lower beta-hydroxybutyrate concentrations throughout, higher leptin concentrations pre-partum and both the peak in non-esterified fatty acids and the nadir in urea concentration occurred earlier after calving. These differences were associated with significantly lower milk production. Leptin concentrations fell at calving and were related to body condition score. Insulin was negatively correlated with yield in MP cows only. In MP cows the relationship between insulin-like growth factor-I and yield switched from negative to positive between weeks +4 and +7. Both beta-hydroxybutyrate and urea were positively related to yield in PP cows. In contrast, in MP cows beta-hydroxybutyrate was negatively correlated with yield and urea was strongly related to body condition score but not yield. These results suggest that there are differences in the control of tissue mobilization between PP and MP cows which may promote nutrient partitioning into growth as well as milk during the first lactation.

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Poor fertility has become a major reason for involuntary culling of dairy cows in the United Kingdom. Calving interval (CI) and body condition score (BCS) are recorded, heritable, genetically correlated with each other, and could be used to extend the scope of dairy indices to include fertility traits. The use of U.K. insemination information for the evaluation of fertility has not been examined previously. Fertility and correlated traits were examined using nationally recorded milk (MILK = daily milk yield at test nearest d 110), BSC, and fertility traits (CI and the insemination traits of nonreturn rate after 56 d, NR56; days to first service, DFS; and number of inseminations per conception, INS). Genetic parameters for the traits were estimated simultaneously with a multitrait sire maternal grandsire (MGS) model and a multitrait BLUP sire MGS model was used to predict sire predicted transmitting abilities for each trait. The relationship between the fertility traits and other predicted transmitting abilities calculated in the United Kingdom was then examined. Heritabilities for the fertility traits were CI = 0.033 +/- 0.01, DFS = 0.037 +/- 0.01, NR56 = 0.018 +/- 0.001, and INS = 0.020 +/- 0.001, with a genetic correlation of 0.671 +/- 0.063 between CI and DFS and -0.939 +/- 0.031 between NR56 and INS. There was an unfavorable genetic correlation between the fertility traits and milk yield and BCS. Predicted transmitting abilities produced are similar in size and range to those produced in other studies and genetic trends are as expected. Results to date are encouraging and suggest that the planned program of work will lead to a fertility index that, when used by breeding companies, will lead to improvements in national dairy cow fertility.

The trend to poorer fertility in dairy cattle with rising genetic merit for production over the last decade suggests that breeding goals need to be broadened to include fertility. This requires reliable estimates of genetic (co)variances for fertility and other traits of economic importance. In the United Kingdom at present, reliable information on calving dates and hence calving intervals are available for most dairy cows. Data in this study consisted of 44,672 records from first lactation heifers on condition score, linear type score, and management traits in addition to 19,042 calving interval records. Animal model REML was used to estimate (co)variance components. Genetic correlations of body condition score (BCS) and angularity with calving interval were -0.40 and 0.47, respectively, thus cows that are thinner and more angular have longer calving intervals. Genetic correlations between calving interval and milk, fat, and protein yields were between 0.56 and 0.61. Records of phenotypic calving interval were regressed on sire breeding values for BCS estimated from records taken at different months of lactation and breeding values for BCS change. Genetic correlations inferred from these regressions showed that BCS recorded 1 mo after calving had the largest genetic correlation with calving interval in first lactation cows. It may be possible to combine information on calving interval, BCS, and angularity into an index to predict genetic merit for fertility.

Variance components were estimated from an animal model using a restricted maximum likelihood procedure which allowed for unequal design matrices and missing observations (VCE). Data sets containing: (i) 15 275 records of linear type classifications on heifers, (ii) 3399 live weight and condition scores measured at calving and (in) 1157 records of yield, dry-matter intake, average live weight and condition score during the first 26 weeks of lactation; were analysed jointly. Heritability estimates for dry-matter intake, live weight and condition score in the largest data set were 0-44, 0-44 and 0-35 respectively and the genetic correlation between condition score and the yield traits ranged from -0-29 to -0-46. The genetic correlation between milk yield and average live weight was negative (-0-09) but after adjusting for the genetic variation in condition score this correlation was positive . Genetic correlations between live weight and stature, chest width, body depth and rump width were consistently high (0-52 to 0-64; 0-75 to 0-86; 0-59 to 0-81; 0-56 to 0-74, respectively). Chest width and body depth were little to moderately correlated with dry-matter intake (0-25 to 0-28 and 0-20 to 0-34 respectively), and angularity (-0-47 to -0-77) and chest width (0-32 to 0-73) appeared to be good predictors of condition score. These correlations showed that (i) the relative value of live weight compared with food intake capacity determines the optimum direction of selection for stature, chest width, body depth and angularity, and consequently the optimum size of the dairy cow, and that (ii) live weight, condition score and food intake can be predicted from the type traits with little loss in accuracy. A restricted index which maintains condition score at its current level was predicted to reduce overall (economic) genetic gain by 5%.