The wide-ranging potential impacts of climate change on both ecology and human infrastructure have led to a large amount of research; however, studies of the projected impacts on agricultural systems have so far focussed mainly on crops. Given the proven adverse effects of extreme weather conditions on the productivity and welfare of livestock, this thesis assesses the potential impact of such a change on the thermal balance of livestock in the UK. A series of mathematical models was designed to predict the metabolic rate and occurrence of thermal stress in sheep and cattle outdoors, and pigs and broiler chickens indoors by solution of the energy balance equations. The models run on commonly-available hourly weather data, and as far as possible were based on the physics of heat and mass transfer rather than empirical relationships. The animals were modelled as systems of geometrical shapes, incorporating the underlying tissue, a coat and the external environment. Physiological responses to hot and cold conditions, including panting, sweating, vasomotor action and shivering were parameterised. Validation of the model output showed good agreement with measured data. The climate predictions for the year 2050 were reduced to synthetic hourly weather data using a stochastic weather generator and several simple downscaling techniques. The climate change impact assessment was made for an upland and a dry lowland site in the UK. There are two main conclusions to the work. First, climate change is predicted to have little effect on ruminants outdoors, or on the suitability of a site for grazing livestock. Second, animals indoors will experience significantly more heat stress under climate change, probably since indoor animals are at greater risk of heat stress in the current climate than those outdoors. In the next fifty years, pig and broiler chicken farms will have to introduce methods for alleviation of heat stress to avoid economic and welfare problems. Future work will need to focus more on collection of accurate heat balance data rather than on more mathematical modelling.
| Identifer | oai:union.ndltd.org:bl.uk/oai:ethos.bl.uk:389354 |
| Date | January 1997 |
| Creators | Turnpenny, John R. |
| Publisher | University of Nottingham |
| Source Sets | Ethos UK |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Source | http://eprints.nottingham.ac.uk/12536/ |
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