The use of GNSS technology to identify lambing behaviour in pregnant grazing Merino ewes

This current study investigated whether pre-lambing behavioural changes could be identified with the use of global navigation satellite system (GNSS) technology. GNSS devices were deployed on 20 pregnant Merino ewes grazing a 1.6 ha paddock and their lambing activity was compared with the metrics derived from the spatial data. The aims were to evaluate the lambing event using the following three separate metrics: (1) mean daily speed (MDS) of ewes 7 days before and to 7 days after lambing, inclusive (n = 12); (2) mean hourly speed (MHS) 12 h before and 12 h after lambing, inclusive (n = 9); and (3) the mean distance the lambing ewe to her peers in the 7 days before and the 7 days after lambing (mean distance to peers (MDP); n = 9), inclusive. There was a significant (P < 0.01) difference between pre- and post-lambing MDS with average +/- se MDS pre-lambing being faster than post-lambing (0.051 +/- 0.0004 vs 0.047 +/- 0.0005 m/s). Pre- and post-lambing MHS differed significantly (P < 0.05), with mean +/- s.e. MHS pre-lambing being faster than post-lambing (0.049 +/- 0.002 vs 0.038 +/- 0.002 m/s). Mean distance to peers indicated that at the time of lambing, ewes were significantly (P < 0.01) further from their peers than at either pre- or post-lambing (83.6 +/- 14.59 vs 35.2 +/- 2.82 vs 35.6 +/- 1.68 m). Despite MDS and MHS metrics indicating significant changes pre- and post-lambing, neither metric was able to identify the time of lambing. The MDP metric could not identify differences pre- and post-lambing but was useful at predicting lambing. The current study found that MD Sand MHS metrics have the potential to determine a 'trigger' point that could identify parturition and therefore could be used to determine the day of lambing. Therefore, further research is required to determine if a combination of these metrics could identify pre-lambing activity that would enable informed management decisions to be made.