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Agent-based modelling of foraging behaviour: the impact of spatial heterogeneity on disease risks from faeces in grazing systems

Published online by Cambridge University Press:  09 September 2008

G. MARION*
Affiliation:
Biomathematics and Statistics Scotland, James Clerk Maxwell Building, The King's Buildings, Edinburgh EH9 3HH, UK
L. A. SMITH
Affiliation:
Scottish Agricultural College, Animal Nutrition and Health Department, West Mains Rd, Edinburgh EH9 3JF, UK
D. L. SWAIN
Affiliation:
CSIRO Livestock Industries, J. M. Rendel Laboratory, Ibis Avenue, North Rockhampton, Qld 4701, Australia
R. S. DAVIDSON
Affiliation:
Scottish Agricultural College, Animal Nutrition and Health Department, West Mains Rd, Edinburgh EH9 3JF, UK
M. R. HUTCHINGS
Affiliation:
Scottish Agricultural College, Animal Nutrition and Health Department, West Mains Rd, Edinburgh EH9 3JF, UK
*
*To whom all correspondence should be addressed. Email: glenn@bioss.ac.uk

Summary

Many of the most pervasive disease challenges to livestock are transmitted via oral contact with faeces (or by faecal–aerosol) and the current paper focuses on how disease risk may depend on: spatial heterogeneity, animal searching behaviour, different grazing systems and faecal deposition patterns including those representative of livestock and a range of wildlife. A spatially explicit agent-based model was developed to describe the impact of empirically observed foraging and avoidance behaviours on the risk of disease presented by investigative and grazing contact with both livestock and wildlife faeces. To highlight the role of spatial heterogeneity on disease risks an analogous deterministic model, which ignores spatial heterogeneity and searching behaviour, was compared with the spatially explicit agent-based model. The models were applied to assess disease risks in temperate grazing systems. The results suggest that spatial heterogeneity is crucial in defining the disease risks to which individuals are exposed even at relatively small scales. Interestingly, however, although sensitive to other aspects of behaviour such as faecal avoidance, it was observed that disease risk is insensitive to search distance for typical domestic livestock restricted to small field plots. In contrast disease risk is highly sensitive to distributions of faecal contamination, in that contacts with highly clumped distributions of wildlife contamination are rare in comparison to those with more dispersed contamination. Finally it is argued that the model is a suitable framework to study the relative inter- and intra-specific disease risks posed to livestock under different realistic management regimes.

Type
Modelling Animal Systems Paper
Copyright
Copyright © 2008 Cambridge University Press

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Footnotes

Current address: Department of Psychology, University of Stirling, Stirling, FKP 4LA, UK.

References

REFERENCES

Arnold, G. E. (1987). Influence of the biomass, botanical composition and sward height of annual pastures on foraging behaviour of sheep. Journal of Applied Ecology 24, 759772.CrossRefGoogle Scholar
Bazely, D. R. (1990). Rules and cues used by sheep foraging in monocultures. In Behavioural Mechanisms of Food Selection (Ed. Hughes, R. N.), pp. 343367. London, UK: Springer.CrossRefGoogle Scholar
Bazely, D. R. & Ensor, C. V. (1989). Discrimination learning in sheep with cues varying in brightness and hue. Applied Animal Behaviour Science 23, 293299.CrossRefGoogle Scholar
Black, J. L. & Kenney, P. A. (1984). Factors affecting diet selection by sheep. 2. Height and density of pasture. Australian Journal of Agricultural Research 35, 565578.CrossRefGoogle Scholar
Dohi, H., Yamada, A. & Entsu, S. (1991). Cattle feeding deterrents emitted from cattle faeces. Journal of Chemical Ecology 17, 11971203.CrossRefGoogle Scholar
Edwards, G. R., Newman, J. A., Parsons, A. J. & Krebs, J. R. (1996) The use of spatial memory by grazing animals to locate food patches in spatially heterogeneous environments: an example with sheep. Applied Animal Behaviour Science 50, 147160.CrossRefGoogle Scholar
Edwards, G. R., Newman, J. A., Parsons, A. J. & Krebs, J. R. (1997). Use of cues by grazing animals to locate food patches: an example with sheep. Applied Animal Behaviour Science 51, 5968.CrossRefGoogle Scholar
Farnsworth, K. D. & Beecham, J. A. (1999). How do grazers achieve their distribution? A continuum of models from random diffusion to the ideal free distribution using biased random walks. American Naturalist 153, 509526.CrossRefGoogle Scholar
Forbes, T. D. A. & Hodgson, J. (1985). The reaction of grazing sheep and cattle to the presence of dung from the same or the other species. Grass and Forage Science 40, 177182.CrossRefGoogle Scholar
Gallagher, J. & Horwill, D. M. (1977). Selective oleic acid albumin agar medium for cultivation of Mycobacterium bovis. Journal of Hygiene 79, 155160.CrossRefGoogle ScholarPubMed
Haynes, R. J. & Williams, P. H. (1993). Nutrient cycling and soil fertility in the grazed pasture ecosystem. Advances in Agronomy 49, 119199.CrossRefGoogle Scholar
Hutchings, M. R. & Harris, S. (1997). Effects of farm management practices on cattle grazing behaviour and the potential for transmission of bovine tuberculosis from badgers to cattle. Veterinary Journal 153, 149162.CrossRefGoogle ScholarPubMed
Hutchings, M. R., Kyriazakis, I., Anderson, D. H., Gordon, I. J. & Coop, R. L. (1998). Behavioural strategies used by parasitised and nonparasitised sheep to avoid ingestion of gastrointestinal nematodes. Animal Science 67, 97106.CrossRefGoogle Scholar
Hutchings, M. R., Athanasiadou, S., Kyriazakis, I. & Gordon, I. J. (2003). Can animals use foraging behaviour to combat parasites? Proceedings of the Nutrition Society 62, 361370.CrossRefGoogle ScholarPubMed
Isham, V. (1991). Assessing the variability of stochastic epidemics. Mathematical Biosciences 107, 209224.CrossRefGoogle ScholarPubMed
Judge, J., Greig, A., Kyriazakis, I. & Hutchings, M. R. (2005). Ingestion of faeces by grazing herbivores – risk of inter-species disease transmission. Agriculture Ecosystems and Environment 107, 267274.CrossRefGoogle Scholar
Keeling, M. J. (2000). Metapopulation moments: coupling, stochasticity and persistence. Journal of Animal Ecology 69, 725736.CrossRefGoogle ScholarPubMed
Krishnarajah, I., Cook, A., Marion, G. & Gibson, G. (2005). Novel moment closure approximations in stochastic epidemics. Bulletin of Mathematical Biology 67, 855873.CrossRefGoogle ScholarPubMed
Langvatn, R. & Hanley, T. A. (1993). Feeding-patch choice by red deer in relation to foraging efficiency. Oecologia 95, 164170.CrossRefGoogle Scholar
Lazo, A. & Soriguer, R. C. (1993). Size-biased foraging behavior in feral cattle. Applied Animal Behaviour Science 36, 99110.CrossRefGoogle Scholar
Marion, G., Swain, D. L. & Hutchings, M. R. (2005). Understanding foraging behaviour in spatially heterogeneous environments. Journal of Theoretical Biology 232, 127142.CrossRefGoogle ScholarPubMed
Marion, G., Walker, D. M., Cook, A., Swain, D. L. & Hutchings, M. R. (2007) Towards an integrated approach to stochastic process-based modelling: with applications to animal behaviour and spatial temporal spread. In Redesigning Animal Agriculture (Eds Swain, D. L., Charmley, E., Steel, J. & Coffey, S.), pp. 144170. Wallingford, UK: CAB International.Google Scholar
Nasell, I. (2003). Moment closure and the stochastic logistic model. Theoretical Population Biology 63, 159168.CrossRefGoogle ScholarPubMed
Parsons, A. J. & Dumont, B. (2003). Spatial heterogeneity and grazing processes. Animal Research 52, 161179.CrossRefGoogle Scholar
Parsons, A. J., Schwinning, S. & Carrėre, P. (2001). Plant growth functions and possible spatial and temporal scaling errors in models of herbivory. Grass and Forage Science 56, 2134.CrossRefGoogle Scholar
Phillips, C. J. C. (1993). Cattle Behaviour. Ipswich, UK: Farming Press Books.Google Scholar
Renshaw, E. (1991). Modelling Biological Populations in Space and Time. Cambridge, UK: Cambridge University Press.CrossRefGoogle Scholar
Schwinning, S. & Parsons, A. J. (1999). The stability of grazing systems revisited: spatial models and the role of heterogeneity. Functional Ecology 13, 737747.CrossRefGoogle Scholar
Swain, D. L., Hutchings, M. R. & Marion, G. (2007). Using a spatially explicit model to understand the impact of search rate and search distance on spatial heterogeneity within a herbivore grazing system. Ecological Modelling 203, 319326.CrossRefGoogle Scholar
Swain, D. L., Friend, M. A., Mayes, R. W., Wilson, L. A. & Hutchings, M. R. (2008). Combining an active transponder system with sprayed n-alkanes to quantify investigative and ingestive grazing behaviour of dairy cattle in pastures treated with slurry. Applied Animal Behaviour Science 109, 211222.CrossRefGoogle Scholar
Ungar, E. D. (1996). Ingestive behaviour. In The Ecology and Management of Grazing Systems (Eds Hodgson, J. & Illius, A. W.), pp. 185218. Wallingford, UK: CAB International.Google Scholar
Walker, D. M., Perez-Barberia, F. J. & Marion, G. (2006). Stochastic modelling of ecological processes using hybrid Gibbs samplers. Ecological Modelling 198, 4052.CrossRefGoogle Scholar
Wallis de Vries, M. F. & Schippers, P. (1994). Foraging in a landscape mosaic: selection for energy and minerals in free ranging cattle. Oecologia 100, 107117.CrossRefGoogle Scholar
Whittle, P. (1957). On the use of the normal approximation in the treatment of stochastic processes. Journal of the Royal Statistical Society B 19, 268281.Google Scholar
Yearsley, J., Hastings, I. M., Gordon, I. J., Kyriazakis, I. & Illius, A. W. (2002). A lifetime perspective on foraging and mortality. Journal of Theoretical Biology 215, 385397.CrossRefGoogle ScholarPubMed