Validation of resilience indicators by estimating genetic correlations among daughter groups and with yield responses to a heat wave and disturbances at herd level

摘要

Resilient cows are minimally affected in their functioningby disturbances, and if affected, they quicklyrecover. Previously, the variance and autocorrelation ofdaily deviations from a lactation curve were proposedas resilience indicators. These traits were heritable andgenetically associated with good health and longevity.However, it was unknown if selection for these indicatorswould lead to desired changes in the phenotype.The first aim of this study was to investigate if forwardprediction of the resilience indicators in another environmentwas possible. Therefore, the resilience indicatorrecords were split into 2 subsets, each containinghalf of the daughters of each sire, split within sire intocows that calved in early year-seasons and cows thatcalved in more recent year-seasons. Genetic correlationsbetween the subsets were then estimated for eachresilience indicator. The second aim was to estimategenetic correlations between the resilience indicatorsand traits describing production responses to actualdisturbances. The disturbances were a heat wave inJuly 2015 and yield disturbances at herd level. Thelatter were selected by decreases in mean yield of allprimiparous cows in a herd, indicating that a disturbanceoccurred. The data set used for calculation ofthe resilience indicators and the traits describing yieldresponses contained 62,932,794 daily milk yield recordson 199,104 primiparous cows. Genetic correlations (r_g)between recent and earlier daughter groups were 1 forboth resilience indicators, which suggests that selectionwill result in changes in the phenotype in the nextgeneration. Furthermore, low variance was geneticallycorrelated with weak response in milk yield to both theheat wave and herd disturbances (r_g 0.47 to 0.97). Lowautocorrelation was genetically correlated with reducedperturbation length and quick recovery after the heatwave and herd disturbances (0.28 to 0.97). These resultssuggest that variance and autocorrelation coverdifferent aspects of resilience, and should be combinedin a resilience index. In conclusion, genetic selection forthe resilience indicators will likely result in favorablechanges in the traits themselves, and in response andrecovery to actual disturbances, which confirms thatthey are useful resilience indicators.