Kym P. Patison

Monitoring Animal Behaviour and Environmental Interactions Using Wireless Sensor Networks, GPS Collars and Satellite Remote Sensing

Remote monitoring of animal behaviour in the environment can assist in managing both the animal and its environmental impact. GPS collars which record animal locations with high temporal frequency allow researchers to monitor both animal behaviour and interactions with the environment. These ground-based sensors can be combined with remotely-sensed satellite images to understand animal-landscape interactions. The key to combining these technologies is communication methods such as wireless sensor networks (WSNs). We explore this concept using a case-study from an extensive cattle enterprise in northern Australia and demonstrate the potential for combining GPS collars and satellite images in a WSN to monitor behavioural preferences and social behaviour of cattle.

Changes in the group associations of free-ranging beef cows at calving

Dyadic association between individuals forms the basis of group structures for herding animals. Group associations and social bonds are dynamic and can result in the establishment of new subgroups. The onset of parturition and the introduction of an offspring create a social change for a mother that is part of a herd. There is a need to nurture the young, develop and maintain a strong maternal bond, and build or maintain social networks within the larger herd. The present study explored associations within a herd of cattle that included pregnant cows and cows with calves (maternal cows). Group dynamics were determined by daily observations of group associations over an 11-week period. During the period, some pregnant cows calved and it was possible to quantify their associations before and post-calving. The associations between individual cows were quantified using a half-weight index (HWI). The HWI data for the maternal and pregnant class of cows were compared. The overall HWI data and the individual class data (pregnant or maternal) were tested against a random model, using data that were generated using permutation methods. There were significant differences in the associations of the pregnant and maternal cows; the maternal cows had stronger associations with other maternal cows while the pregnant cows showed evidence of weaker associations with other pregnant cows and the maternal cows. As pregnant cows calved, they developed stronger associations with other maternal cows. The present study provided evidence that pregnant cows prefer to maintain a degree of isolation, but strengthen their social bonds with other mothers as they enter a maternal phase.

Time is of the essence: an application of a relational event model for animal social networks

Understanding how animal social relationships are created, maintained and severed has ecological and evolutionary significance. Animal social relationships are inferred from observations of interactions between animals; the pattern of interaction over time indicates the existence (or absence) of a social relationship. Autonomous behavioural recording technologies are increasingly being used to collect continuous interaction data on animal associations. However, continuous data sequences are typically aggregated to represent a relationship as part of one (or several) pictures of the network of relations among animals, in a way that parallels human social networks. This transformation entails loss of information about interaction timing and sequence, which are particularly important to understand the formation of relationships or their disruption. Here, we describe a new statistical model, termed the relational event model, that enables the analysis of fine-grained animal association data as a continuous time sequence without requiring aggregation of the data. We apply the model to a unique data set of interaction between familiar and unfamiliar steers during a series of 36 experiments to investigate the process of social disruption and relationship formation. We show how the model provides key insights into animal behaviour in terms of relationship building, the integration process of unfamiliar animals and group building dynamics. The relational event model is well suited to data structures that are common to animal behavioural studies and can therefore be applied to a range of social interaction data to understand animal social dynamics.

Using temporal associations to determine maternal parentage in extensive beef herds

The assignment of maternal parentage, although time-consuming and expensive using traditional methods, is essential for genetic improvement. Within the sheep industry the recording of time-based (temporal) associations without human intervention has been routinely used to derive maternal parentage, however it has not been researched in extensive beef production systems. To determine whether temporal associations could be used to assign maternal parentage, cows and calves had their identity recorded as they walked to water over a 27-day trial. Two methods of association were investigated, being the half-weight index and the time difference between a cow and calf having their identity recorded. The half-weight index, which is a measure of the number of times two individuals are recorded together, correctly assigned greater than 90% of maternal pairs. When investigating the duration of data recording it was shown that 85% of maternal parentage could be achieved within only 21 days. Further work is required to determine the effect of calf age, herd and paddock size; however, the results showed that the half-weight index method of determining maternal associations is a labour-saving and accurate alternative to traditional methods used to identify maternal parentage.

A scoping study to assess the precision of an automated radiolocation animal tracking system

The mean spatial precision for the ARATS ear tags was ?22m.Signal propagation effects and meteorological parameters affected spatial precision.The time between transmissions showed no effect on the spatial precision. The spatial precision of a new automated radiolocation animal tracking system (ARATS) was studied in a small-scale (~5ha) trial site. Twelve static tags, in a four by three grid, transmitted for 28days. The 12 tags recorded 36,452 transmissions with a mean transmission per tag of 3037. Each transmission included the tag number, date and time and the calculated longitude and latitude. The mean location and then the Euclidean distance from the mean location for each tag were calculated in order to derive location precision per tag. The overall precision for the 12 tags was ?22m with a SD of 49m with the most and least precise tags having precisions of ?8m and ?51m, respectively. As with other geolocation technologies, it would appear that structures in the environment cause signal propagation effects including multipath and non-line-of-sight, which result in errors in the derived locations.The distance from the mean data was log transformed (log10) and summarised in order to present all data over a 24-h period. There was a statistically significant decrease in precision between 11:00 and 17:00h. These data were correlated with meteorological parameters for the period of the trial, again summarised over 24h, with temperature, humidity, wind speed and pressure all having significant correlations with the precision data.The variance between individual tag transmissions were compared to see whether the distance between derived locations increased as time between transmissions increased. The means for each tag showed the same variance as the mean precision values, that is the more precise tags had lower means and the less precise tags had higher means. However, no tags showed a trend towards an increase in the distance between locations as the time between transmissions increased.In order to assess whether there was any spatial variability in the derived locations, the variability in distance between tags was compared for all tag combinations. Tags that were proximal to each other had shorter distances between the mean derived locations and less variance, whereas tags farther apart had large distances and large variance in the mean derived locations.The ARATS assessed in this static evaluation showed a lower level of spatial precision than commercially available global positioning systems. However the system could still have application when used to derive proximal associations between animals in low stocking-rate, extensive grazing situations such as are present in northern Australia.

Using temporal associations to determine postpartum oestrus in tropical beef cows

The radio frequency identification (RFID) technology introduced with the National Livestock Identification System has increased the precision of livestock management. Tag readers incorporated in walk-over-weighing systems have enabled automated collection of daily RFID sequential data as cattle access water. The temporal sequence of individuals accessing a watering point in a rangeland grazing system could potentially provide knowledge of key aspects of animal behaviour. The current study investigated the use of the shortest daily average interval of time from cow to bull (TTB) coming to water over a 29-day period to predict postpartum oestrus events. Fifteen Brahman and 15 Belmont Red cows mated to bulls of the same breed in separate paddocks were fitted with proximity loggers, heat-mount detectors and were ovarian-scanned with ultrasonics to determine the timing of postpartum oestrus. The data collected from these devices were compared with RFID sequence data of the bulls following cows to water to evaluate whether TTB alone could predict oestrus activity. At the start of the experimental period, mean (±s.d.) weight and days postpartum of the Brahman cows were 527 (±43.4) kg and 89 (±18.4) days respectively, and of the Belmont Red cows 513 (±54.1) kg and averaged 66 (±19.6) days postpartum. Six of the 15 Brahman cows and 9 of the 15 Belmont Red cows displayed oestrus activity, as indicated by increased contact with the bull, an activated heat-mount detector and the presence of an ovarian corpus luteum. The sensitivity and specificity of TTB as an indicator of oestrus events across the groups were 0.65 and 0.60 respectively. Temporal sequence data have the potential to contribute to the determination of oestrus and date of conception.

Using Walk-over-Weighing technology for parturition date determination in beef cattle

The northern Australian beef industry is dominated by cow-calf operations where reproductive efficiency is a major profit driver. The postpartum anoestrus interval is a major contributor to an animal’s reproductive efficiency and is influenced by genetic selection. The genetic trait that measures an animal’s postpartum anoestrus interval is the days to calving estimated breeding value and a key requirement is knowledge of the cow’s calving date. Traditionally calving date is recorded using laborious and costly methods that are impeding the recording and hence the accuracy of genetic predictions for this trait by the northern Australian seedstock industry. The present experiment used Walk-over-Weighing technology to automatically record animal weights as cattle enter a restricted area where they access water. With the use of a novel method to accurately assess weights, the growth paths of cows were tracked from late gestation to post-calving. The calving date was visualised in the growth paths of most cows (78.3%) and a custom algorithm was able to automatically detect the calving date within 10 days of the observed calving period for 63% of cows. The use of Walk-over-Weighing to record calving date provides the opportunity to increase the recording of the days to calving estimated breeding value in the northern seedstock industry, thereby increasing reproductive efficiency and improving the profitability of northern beef producers.