Hostname: page-component-78c5997874-lj6df Total loading time: 0 Render date: 2024-11-08T02:57:47.714Z Has data issue: false hasContentIssue false
  • English
  • Français

Detail and the devil of on-farm parasite control under climate change

Published online by Cambridge University Press:  23 October 2013

Eric R. Morgan
Eric R. Morgan*
Affiliation:
University of Bristol, School of Veterinary Sciences, Langford House, Langford, North Somerset, BS40 5DU, UK
*
Email: [email protected]
Get access Rights & Permissions [Opens in a new window]

Abstract

Levels and seasonal patterns of parasite challenge to livestock are likely to be affected by climate change, through direct effects on life cycle stages outside the definitive host and through alterations in management that affect exposure and susceptibility. Net effects and options for adapting to them will depend very strongly on details of the system under consideration. This short paper is not a comprehensive review of climate change effects on parasites, but rather seeks to identify key areas in which detail is important and arguably under-recognized in supporting farmer adaptation. I argue that useful predictions should take fuller account of system-specific properties that influence disease emergence, and not just the effects of climatic variables on parasite biology. At the same time, excessive complexity is ill-suited to useful farm-level decision support. Dealing effectively with the ‘devil of detail’ in this area will depend on finding the right balance, and will determine our success in applying science to climate change adaptation by farmers.

Keywords

parasitehelminthdiseaseepidemiologyclimate changedecision supportlivestock
Type
Review Article
Information
Animal Health Research Reviews , Volume 14 , Issue 2 , December 2013 , pp. 138 - 142
Copyright
Copyright © Cambridge University Press 2013 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Besier, RB (2012). Refugia-based strategies for sustainable worm control: factors affecting the acceptability to sheep and goat owners. Veterinary Parasitology 186: 2–9.CrossRefGoogle ScholarPubMed
Cornell, S (2005). Modelling nematode populations: 20 years of progress. Trends in Parasitology 21: 542–545.CrossRefGoogle ScholarPubMed
Dobson, ADM, Finnie, TJR and Randolph, SE (2011). A modified matrix model to describe the seasonal population ecology of the European tick Ixodes ricinus. Journal of Applied Ecology 48: 1017–1028.CrossRefGoogle Scholar
Fox, NJ, White, PCL, McClean, CJ, Marion, G, Evans, A and Hutchings, MR (2011). Impacts of climate change on Fasciola hepatica risk. PLoS ONE 6: e16126.CrossRefGoogle ScholarPubMed
Grenfell, BT, Smith, G and Anderson, RM (1986). Maximum likelihood estimates of the mortality and migration rates of the infective larvae of Ostertagia ostertagi and Cooperia oncophora. Parasitology 92: 643–652.CrossRefGoogle ScholarPubMed
Kahn, LP and Woodgate, RG (2012). Integrated parasite management: products for adoption by the Australian sheep industry. Veterinary Parasitology 186: 58–64.CrossRefGoogle ScholarPubMed
Kaplan, R (2004). Drug resistance in nematodes of veterinary importance: a status report. Trends in Parasitology 20: 477–481.Google Scholar
Kenyon, F and Jackson, F (2012). Targeted flock/herd and individual ruminant treatment approaches. Veterinary Parasitology 186: 10–17.CrossRefGoogle ScholarPubMed
Laurenson, YCSM, Kyriazakis, I, Forbes, AB and Bishop, SC (2012). Exploration of the epidemiological consequences of resistance to gastro-intestinal parasitism and grazing management of sheep through a mathematical model. Veterinary Parasitology 189: 238–249.Google Scholar
Laurenson, YCSM, Bishop, SC, Forbes, AB and Kyriazakis, I (2013). Modelling the short- and long-term impacts of drenching frequency and targeted selective treatment on the performance of grazing lambs and the emergence of anthelmintic resistance. Parasitology 140: 780–791.CrossRefGoogle Scholar
Learmount, J, Taylor, MA, Smith, G and Morgan, C (2006). A computer model to simulate control of parasitic gastroenteritis in sheep on UK farms. Veterinary Parasitology 142: 312–329.CrossRefGoogle ScholarPubMed
Leger, E, Vour'h, G, Vial, L, Chevillon, C and McCoy, KD (2013). Changing distributions of ticks: causes and consequences. Experimental and Applied Acarology 59: 219–244.CrossRefGoogle ScholarPubMed
Marshall, NA (2010). Understanding social resilience to climate variability in primary enterprises and industries. Global Environmental Change – Human and Policy Dimensions 20: 36–43.CrossRefGoogle Scholar
Morgan, ER, Milner-Gulland, EJ, Torgerson, PR and Medley, GF (2004). Ruminating on complexity: macroparasites of wildlife and livestock. Trends in Ecology and Evolution 19: 181–188.Google Scholar
Ogden, NH, Lindsay, LR and Leighton, PA (2013) Predicting the rate of invasion of the agent of Lyme disease Borrelia burgdorferi. Journal of Applied Ecology 50: 510–518.Google Scholar
Ollerenshaw, CB and Rowlands, WT (1959) A method of forecasting the incidence of fascioliasis in Anglesey. Veterinary Record 71: 591–598.Google Scholar
O'Connor, LJ, Kahn, LP and Walkden-Brown, SW (2008). Interaction between the effects of evaporation rate and amount of simulated rainfall on development of the free-living stages of Haemonchus contortus. Veterinary Parasitology 155: 223–234.CrossRefGoogle ScholarPubMed
Paaijmans, KP, Read, AF and Thomas, MB (2009). Understanding the link between malaria risk and climate. Proceedings of the National Academy of Sciences of the United States of America 106: 13844–13849.CrossRefGoogle ScholarPubMed
Ploeger, HW, van Doorn, DCK, Nijsse, ER and Eysker, M (2008). Decision trees on the web: a parasite compendium. Trends in Parasitology 24: 203–204.Google Scholar
Roberts, MG and Grenfell, BT (1991). The population dynamics of nematode infections of ruminants: periodic perturbations as a model for management. IMA Journal of Mathematics Applied in Medicine and Biology 8: 83–93.CrossRefGoogle Scholar
Smith, G and Grenfell, BT (1994). Modelling of parasite populations: gastrointestinal nematode models. Veterinary Parasitology 54: 127–143.CrossRefGoogle ScholarPubMed
Smith, LP and Thomas, RJ (1972). Forecasting spring hatch of Nematodirus battus by use of soil temperature data. Veterinary Record 90: 388–392.Google Scholar
Smith, S, Ward, V and House, A (2011). ‘Impact’ in the proposals for the UK's research excellence framework: shifting the boundaries of academic autonomy. Research Policy 40: 1369–1379.CrossRefGoogle Scholar
Van Dijk, J and Morgan, ER (2010). Variation in the hatching behavior of Nematodirus battus: polymorphic bet hedging? International Journal for Parasitology 40: 675–681.CrossRefGoogle ScholarPubMed
Van Dijk, J, David, GP, Baird, G and Morgan, ER (2008). Back to the future: developing hypotheses on the effects of climate change on ovine parasitic gastroenteritis from historical data. Veterinary Parasitology 158: 73–84.CrossRefGoogle Scholar
Van Dijk, J, de Louw, MDE, Kalis, LPA and Morgan, ER (2009). Ultraviolet light increases mortality of nematode larvae and can explain patterns of availability at pasture. International Journal for Parasitology 39: 1151–1156.CrossRefGoogle ScholarPubMed
Van Wyk, JA (2001). Refugia: overlooked as perhaps the most potent factor concerning the development of anthelmintic resistance. Onderstepoort Journal of Veterinary Research 68: 55–67.Google ScholarPubMed
Wall, R, Cruickshank, I, Smith, KE, French, NP and Holme, AS (2002). Development and validation of a simulation model for blowfly strike of sheep. Medical and Veterinary Entomology 16: 335–346.Google Scholar
Wall, R, Rose, H, Ellse, L and Morgan, E (2011). Livestock ectoparasite management in a changing climate. Veterinary Parasitology 180: 82–89.CrossRefGoogle Scholar
Woodgate, RG and Love, S (2012). Womkill to wormboss: can we sell sustainable sheep worm control? Veterinary Parasitology 186: 51–57.CrossRefGoogle ScholarPubMed