Halasz A.1, Nagy G.2, Tassi J.1 and Bajnok M.1
1Szent Istvan University, Faculty of Agriculture and Environmental Studies, Institute of Crop Production, 2100 Godollo, 1. Pater Karoly rd., Hungary; 2University of Debrecen, Faculty of Economics, Department of Rural Development and Regional Economics, 4032 Debrecen, 138. Boszormenyi rd., Hungary;
halasz.andras@mkk.szie.hu
Abstract
Behaviour of Hungarian grey cattle was observed under range grazing conditions during four grazing seasons. The actual behaviour of cattle was recorded 3 times an hour, during investigated grazing days.
Selected animals were tagged with GPS recorders which made it possible to detect their position on the pasture and to calculate the daily covered distance. Detected behavioural traits were recorded in behavioural journals (ethograms). These records allowed us to describe the animals’ detailed daily routine.
The daily behavioural pattern was built up from feed intake-metabolic (47.7%), social (25.9%), move (23.1%) and sexual (3.3%) behaviour traits. New traits (watch, sentinel, threefold division) were revealed and redefined (for this breed only), contrasting with previously published papers. The daily travelled distance covered by cattle, ranged between 1-5 kilometres. It was mostly influenced by the weather-front changes throughout barometric pressure dynamics. Grazing preference showed remarkable differences.
Sward quality and the proximity of water had the greatest influence on the intensity of pasture use.
Keywords: cattle, behaviour, daily routine, daily travelled distance, grazing preference
Introduction
Hungarian grey cattle is a traditional breed with wide environmental tolerance that is well adapted for extensive rangelands and pastoral grazing. In the 1970’s (Bodo et al., 1979) the first behavioural studies revealed the general behavioural traits. These observations mainly focused on reproductional behaviour.
We considered further relations from a biometerological point of view, like behavioural reactions on different weather conditions. We hypothesized that there are more behavioural traits existing than previously described. Furthermore, we hypothesized that individual weather factors have significant effects on cattle behaviour in rangeland, the grass supply has significant influence on grazing-metabolic behaviour and the spatial variation of Hungarian grey cattle is not consistent.
Materials and methods
The observed herd contained different age groups, mostly mid-age cows and their calves, but from May to August bulls made their own groups as well. We have recorded daily ethograms about the marked cows regarding behavioural traits (grazing, resting, ruminating, drinking, social interactions, moving). The herds are roaming on big pastures without restrictions. We had 10 observed cows (out of 200) marked with coloured ropes for visual identification. The cows kept 50-100 m flight-zone, therefore high vis-markers were essential. The herd did not receive supplementary feed during the grazing seasons and in winter time housing, only hay and salt was fed. The study area was 1,191 ha rangeland 5 km South-west from Hortobagy village, Hungary. Hortobagy River and two local shadoofs (dug well) provided water. The pasture had sodic soil, fertility was poor, therefore heterogenous plant cover dominated. Three yield categories (none: <100 g m-2, low: 100-300 g m-2, acceptable: 300 g m-2<) were derived from the Hungarian grass-qualification system (Nagy, 2003).
Czako (1985) terminology has been applied to describe the animal behaviour and the behavioural traits were organised in 4 main categories. Animal behaviour was observed periodically, in every 20 minutes, and the duration of recording was approximately 5 seconds each. The most typical behaviour pattern was logged. Every grazing season 30 days (between March-November) were picked to gather behavioural and vegetation data. Meteorological data were collected from the national meteo survey database and we also made local measurements (barometric pressure, temperature). The statistical analysis was conducted by SPSS 20 software pack. Using Gere’ (2003), Ungar et al.’(2005) and Botheras’ (2010) methods, we created an activity graph, registered inactivity at the time when cows slept, rested or did not ruminate while standing. Activity was counted when feeding, drinking, movement or sexual events occured. Two type of GPS receivers have been used (Snewi Trekbox, Bluetooth, GT-750 GPS data logger). The cows grazing preference was observed at the Southern pasture (Malomhazi-pasture), during the 6 hour long (3-3 hours morning-evening) grazing period. We have counted how many cows grazed and for how long in each quadrat and assigned these in four categories (low-medium-high-very high preference). The Livestock Hour Index (LHI) (Trotter, 2009) was calculated:
Results
Based on previous studies we created our own behavioural main categories (feed intake-metabolic; move;
social; sexual). We have described the watch (cows, disturbed by human approach or predators, stop the actual behaviour and monitor the possible dangers) and the sentinel (chosen by dominance and position in the herd; these cows are guarding the group and continuously observing the environment) behavioural traits as the Hungarian grey cattle herd has its own organisation and hierarchy. We also specified the 3-parts dispersion within the herd. This behaviour occurs only in large fields and strongly depends from hierarchical positions. We proved that at low barometric pressure conditions (P≤1000 hPa), the herd is less active and the feed intake-metabolic behaviour is underrepresented.
There are correlations between feed intake-metabolic and move behaviours and barometric pressure (r=0.389, P≤0.05). We determined which Peczely-front types (Peczely, 1961) are the most responsible for the behavioural changes. Prior to the observation day and the following day’s front were significantly affecting behaviour. The feed intake-metabolic behaviour traits appeareance follows the next day front type (r=0.445, P=0.007). The most feed intake-metabolic events happened during the anticyclone over Carpathian-basin (A). There were major effects of the anticyclones from West (Aw) (P=0.049) and North (An) as well. We have observed similar events at categories of move (P=0.004) and social (P=0.039). In both cases the high pressure local-anticyclone and the northern-anticyclone caused the highest event numbers. The average temperature, barometric pressure, humidity, wind speed and wind direction have no significant effect on the four main behavioural categories. Examining the relationship between grass supply and animal behaviour (Table 1), a significant relation was found between the event number of feed intake-metabolic group and grass supply of the area (P=0.033).
According to LHI, we determined the preferred places of residence at Malomhazi pasture. The observed animals stayed 1-2 hours at low (LHI ≤ 0.09) or moderately (LHI: 0.1-0.19) preferred cells. However, most of the visited quadrats were included in the medium preferred group. This finding can mainly be explained by the large extent of this group. The cattle spent most of their time at the northern part of Malomházi pasture (LHI ≥ 0.4), frequently camping daily here. In accordance with the literature, spatial variation was mainly influenced by proximity to water sources, spread of tussock grass and acceptable grass supply (at least 6 cm and 300 g m-2).
pasture had sodic soil, fertility was poor, therefore heterogenous plant cover dominated. Three yield categories (none: <100 g m-2, low: 100-300 g m-2, acceptable: 300 g m-2<) were derived from the Hungarian grass-qualification system (Nagy, 2003).
Czako (1985) terminology has been applied to describe the animal behaviour and the behavioural traits were organised in 4 main categories. Animal behaviour was observed periodically, in every 20 minutes, and the duration of recording was approximately 5 seconds each. The most typical behaviour pattern was logged. Every grazing season 30 days (between March-November) were picked to gather behavioural and vegetation data. Meteorological data were collected from the national meteo survey database and we also made local measurements (barometric pressure, temperature). The statistical analysis was conducted by SPSS 20 software pack. Using Gere’ (2003), Ungar et al.’(2005) and Botheras’ (2010) methods, we created an activity graph, registered inactivity at the time when cows slept, rested or did not ruminate while standing. Activity was counted when feeding, drinking, movement or sexual events occured. Two type of GPS receivers have been used (Snewi Trekbox, Bluetooth, GT-750 GPS data logger). The cows grazing preference was observed at the Southern pasture (Malomhazi-pasture), during the 6 hour long (3-3 hours morning-evening) grazing period. We have counted how many cows grazed and for how long in each quadrat and assigned these in four categories (low-medium-high-very high preference). The Livestock Hour Index (LHI) (Trotter, 2009) was calculated:
LHI (Livestock Hour Index) = �𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺𝐺 𝑇𝑇𝑇𝑇𝐺𝐺𝐺𝐺𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 (ℎ𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝑜𝐺𝐺𝐺𝐺)
𝐶𝐶𝐶𝐶𝑜𝑜𝑜𝑜𝐶𝐶𝐶𝐶 (ℎ𝑇𝑇𝑇𝑇𝐺𝐺𝐺𝐺𝑒𝑒𝑒𝑒) � ÷ 𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔𝑔/𝑔𝑔𝑔𝑔𝑑𝑑𝑑𝑑𝑑𝑑𝑑𝑑 low ≤ 0,1; medium 0,1 – 0,2; high 0,2 – 0,4; very high ≥ 0,4
Results
Based on previous studies we created our own behavioural main categories (feed intake-metabolic; move; social; sexual). We have described the watch (cows, disturbed by human approach or predators, stop the actual behaviour and monitor the possible dangers) and the sentinel (chosen by dominance and position in the herd theese cows are guarding the group and continuously observing the environment) behavioural traits as the Hungarian grey cattle herd has its own organisation and hierarchy. We also specified the 3-parts dispersion within the herd. This behaviour occurs only in large fields and strongly depends from hierarchical positions. We proved that at low barometric pressure conditions (P≤1000 hPa), the herd is less active and the feed intake-metabolic behaviour is underrepresented.
There are correlations between feed intake-metabolic and move behaviours and barometric pressure (r=0.389, p≤0.05). We determined which Peczely-front types (Peczely, 1961) are the most responsible for the behavioural changes. Prior to the observation day and the following day’s front were significantly affecting behaviour. The feed intake-metabolic behaviour traits appeareance follows the next day front type (r=0.445, p=0.007). The most feed intake-metabolic events happened during the anticyclone over Carpathian-basin (A). There were major effects of the anticyclones from West (Aw) (p=0.049) and North (An) as well. We have observed similar events at categories of move (p=0.004) and social (p=0.039). In both cases the high pressure local-anticyclone and the northern-anticyclone caused the highest event numbers. The average temperature, barometric pressure, humidity, wind speed and wind direction have no significant effect on the four main behavioural categories. Examining the relationship between grass supply and animal behaviour (Table 1), a significant relation was
Conclusions
Incoming weather fronts affect on local pressure conditions and presumably the atmospheric electric environment as well. We proved that behaviour depends from pre-front weather conditions and Hungarian grey cattle prefer the pastures with yield 300 g m-2 or more. If grazing animals significantly react on pre-frontal weather systems, this could be used for management purposes as a behavioural forecast. Veterinary inspection could be less stressfull when high barometric pressure prevails.
References
Bodo, I. David, I. and Gothard, L. (1979) A magyar szürke szarvasmarha viselkedése és tartáskörülményei a Hortobágyi Nemzeti Parkban. MTA pályázat, Debrecen.
Botheras, N. (2010) The Feeding Behavior of Dairy Cows: Considerations to Improve Cow Welfare and Productivity. Tri-State Dairy Nutrition 2007.
Czako, J. Keszthelyi, T. and Santha, T. (1985) Etológia Kislexikon. Natura kiadó 113(3), 32.
Gere, T. (2003) Gazdasági állatok viselkedése II. A szarvasmarha viselkedése, 211 pp.
Nagy, G. (2003) A gyepterületek mezőgazdasági értékének meghatározása: Legeltetéses állattartást! In: Tudományos ülés Vinczeffy I.
prof. 80. születésnapja tiszteletére. Konferencia helye, ideje: Debrecen, Magyarország, 2003 Debrecen, pp. 271-280.
Peczely, Gy. (1961) Magyarország makroszinoptikus helyzeteinek éghajlati jellemzése. Az Országos Meteorológiai Intézet Kisebb Kiadványai 32, 158.
Trotter, M.G. Lamb, D. W. and Hinch, G. N. (2009) GPS livestock tracking: a pasture utilisation monitor for the grazing industry.
Proceedings of the 24th Annual Conference of the Grassland Society of NSW, pp. 124-125.
Ungar, E. Henkin, Z. Gutman, M. Dolev, A. Genizi, A. and Ganskopp, D. (2005) Inference of Animal Activity From GPS Collar Data on Free-Ranging Cattle. Rangeland Ecology Management 58, 256-266.
Table 1. Relations between grass supply and the most frequent behavioural traits and groups.1 Grass supply category Behavioral trait
Feed intake-metabolic2 Moving Social
A B C D Average no. of
events
P Avg. no. of
events
P Watch Scratch Average no. of events
P
None 0 10 0 0 30.3±11.8 0.033* 20 15.1±2.2 0.964 0 0 30.83±2.3 0.304
Low 109 158 63 7 29.7±8.1 156 24 9
Acceptable 255 173 121 47 52.8±5.3 226 30 31
1 P = from Kruskal-Wallis test (level of significance: P≤0.05).
2 A = graze (standing); B = graze (in motion); C = ruminate (lying); D = ruminate (standing).