Temporal Aspects of the Development of Root Disease Epidemics

  • C. A. Gilligan

Abstract

Rather like an iceberg, much of the temporal dynamics of root disease epidemics remains hidden. Beneath the surface, there is a rich mass of inter- and intraspecific interactions that determine the dynamics of infection, disease, loss of yield and the generation and carryover of inoculum. The temporal dynamics of some of these interactions are discussed in this chapter. The roles of primary and secondary infection, of root growth and of survival of inoculum as well as antagonism by other microorganisms are examined. Some of the practical constraints imposed on epidemiological analyses by the shortage of data are also considered.

Keywords

Biomass Convection Straw Fusarium Allo 

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References

  1. Anderson RM (ed) (1982) Population dynamics of infectious diseases: theory and applications. Chapman & Hall, LondonGoogle Scholar
  2. Anderson RM, May RM (1979) Population biology of infectious diseases. Part I. Nature 280: 361–367PubMedCrossRefGoogle Scholar
  3. Anderson RM, May RM (1981) The population dynamics of microparasites and invertebrate hosts. Philos Trans R Soc 291: 451–524CrossRefGoogle Scholar
  4. Bailey NTJ (1975) The mathematical theory of infectious diseases and its applications. Academic Press, New YorkGoogle Scholar
  5. Baker KF, Cook PJ (1974) Biological control of plant pathogens. Freeman, San FranciscoGoogle Scholar
  6. Bazin MJ, Markham P, Scott EM, Lynch M (1990) Population dynamics and rhizosphere interactions. In: Lynch J (ed) The rhizosphere. Wiley, Chichester, pp 99–127Google Scholar
  7. Bloomberg WJ (1979) A model of damping-off and root rot of Douglas-fir seedlings caused by Fusarium oxysporum. Phytopathology 69: 1072–1077CrossRefGoogle Scholar
  8. Brassett PR, Gilligan CA (1988) A model for primary and secondary infection in botanical epidemics. Z Pflanzenkr Pflanzenschutz 95: 352–360Google Scholar
  9. Butler FC (1959) Saprophytic behaviour of some cereal root rot fungi. III. Saprophytic survival in soils at high and low fertility. Ann Appl Biol 47: 28–36CrossRefGoogle Scholar
  10. Campbell CL (1986) Interpretation and uses of disease progress curves for root diseases. In: Leonard KJ, Fry WE (eds) Plant disease epidemiology: population dynamics and management, vol I. Macmillan, New York, pp 38–54Google Scholar
  11. Campbell CL, Reynolds KM, Madden LV (1988) Modelling epidemics of root diseases and development of simulators. In: Kranz J, Rotem J (eds) Techniques in plant disease epidemiology. Springer, Berlin Heidelberg New York, pp 253–265Google Scholar
  12. Campbell CL, Madden LV (1990) Introduction to plant disease epidemiology. Wiley, New YorkGoogle Scholar
  13. Coley-Smith JA, Entwistle AR (1988) Susceptibility of garlic to Sclerotium cepivorum. Plant Pathol 37: 261–264CrossRefGoogle Scholar
  14. Deacon JW (1976) Biological control of the take-all fungus, Gaeumannomyces graminis, by Phialophora radicicola and similar fungi. Soil Biol Biochem 8: 275–283CrossRefGoogle Scholar
  15. Ferrin DM, Mitchell DJ (1986) Influence of soil water status on the epidemiology of tobacco black shank. Phytopathology 76: 1213–1217CrossRefGoogle Scholar
  16. Fisher RA, Yates F (1974) Statistical tables for biological, agricultural and medical research. 6th edn. Oliver & Boyd, EdinburghGoogle Scholar
  17. Gilligan CA (1983) Modeling of soilborne pathogens. Annu Rev Phytopathol 21: 45–64CrossRefGoogle Scholar
  18. Gilligan CA (1985a) Probability models for host infection by soilborne fungi. Phytopathology 75: 61–67CrossRefGoogle Scholar
  19. Gilligan CA (1985b) Construction of temporal models. III. Disease progress of soilborne pathogens. In: Gilligan CA (ed) Mathematical modelling of crop disease. Advances in plant pathology, vol 3. Academic Press, London, pp 67–105Google Scholar
  20. Gilligan CA (1990a) Mathematical modelling and analysis of soilborne pathogens. In: Kranz J (ed) Epidemics of plant diseases: mathematical modelling and analysis. 2nd edn. Springer, Berlin Heidelberg New York, pp 96–142Google Scholar
  21. Gilligan CA (1990b) Comparison of disease progress curves. New Phytol 115: 223–242CrossRefGoogle Scholar
  22. Gilligan CA (1990c) Antagonistic interactions involving plant pathogens: fitting and analysis of models to non-monotontic curves for population and disease dynamics. New Phytol 115: 649–665CrossRefGoogle Scholar
  23. Gilligan CA (1990d) Mathematical models of infection. In: Lynch J (ed) The rhizosphere. Wiley, Chichester, pp 207–232Google Scholar
  24. Greenberger A, Yogev A, Katan J (1987) Induced suppressiveness in solarized soils. Phytopathology 77: 1663–1667CrossRefGoogle Scholar
  25. Guttierez AP, DeVay JE (1986) Studies of plant-pathogen-weather interactions: cotton and verticillium wilt. In: Leonard KJ, Fry WE (eds) Plant disease epidemiology: population dynamics and management, vol I. Macmillan, New York, pp 205–231Google Scholar
  26. Guttierez AP, DeVay JE, Pullman GS, Frieberthauser GE (1983) A model of verticillium wilt in relation to cotton growth and development. Phytopathology 73: 89–95CrossRefGoogle Scholar
  27. Hallam TH (1986) Population dynamics in a homogeneous environment. In: Hallam TH, Levin SA (eds) Biomathematics, vol 17. Mathematical ecology. Springer, Berlin Heidelberg New York, pp 62–94Google Scholar
  28. Hassell (1981) Arthropod predator-prey systems. In: May RM (ed) Theoretical ecology: principles and applications. 2nd edn. Blackwell, Oxford, pp 105–131Google Scholar
  29. Hau B (1990) Analytical models of plant disease in a changing environment. Annu Rev Phytopathol 28: 221–245CrossRefGoogle Scholar
  30. Hau B, Eisensmith SP, Kranz J (1985) Construction of temporal models. II. Simulation of aerial epidemics. In: Gilligan CA (ed) Mathematical modelling of crop disease. Advances in plant pathology, vol 3. Academic Press, London, pp 31–65Google Scholar
  31. Hethcote HW (1989) Three basic epidemiological models. In: Levin SA, Hallam TG, Gross LJ (eds) Applied mathematical ecology, Springer, Berlin Heidelberg New York, pp 119–144Google Scholar
  32. Hooker WJ (1956) Foliage fungicides for potatoes in Iowa. Am Potato J 33: 47–52CrossRefGoogle Scholar
  33. Hornby D (1981) Inoculum. In: Asher MJC, Shipton PJ (eds) Biology and control of take-all. Academic Press, London, pp 271–293Google Scholar
  34. Hornby D, Bateman RW, Brown ME, Henden DR (1989) An experimental design and procedures for testing putative controls against naturally-occurring take-all in the field. Ann Appl Biol 115: 195–208CrossRefGoogle Scholar
  35. Hornby D, Henden DR (1980) Take-all decline. Rothamsted Experimental Report for 1979, Part 1. Rothamsted Experiment Station, Rothamsted, pp 184–193Google Scholar
  36. Huisman OJ (1982) Interrelations of root growth dynamics to epidemiology of root-invading fungi. Annu Rev Phytopathol 20: 303–327CrossRefGoogle Scholar
  37. Jeger MJ (1982) The relation between total, infectious, and postinfectious diseased plant tissue. Phytopathology 72: 1185–1189CrossRefGoogle Scholar
  38. Jeger MJ (1984) Relation between rate parameters and latent and infectious periods during a plant disease epidemic. Phytopathology 74: 1148–1152CrossRefGoogle Scholar
  39. Jeger MJ (1986a) Asymptotic behaviour and threshold criteria in model plant disease epidemics. Plant Pathol 35: 355–361CrossRefGoogle Scholar
  40. Jeger MJ (1986b) The potential of analytic compared with simulation approaches to modeling in plant disease epidemiology. In: Leonard KJ, Fry WE (eds) Plant disease epidemiology: population dynamics and management, vol I. Macmillan, New York, pp 255–281Google Scholar
  41. Jeger MJ (1987) The influence of root growth and inoculum density on the dynamics of root disease epidemics: theoretical analysis. New Phytol 107: 459–478CrossRefGoogle Scholar
  42. Jeger MJ, Starr JL (1985) A theoretical model of the winter survival dynamics of Meloidogyne spp. eggs and juveniles. J Nematol 17: 257–260PubMedGoogle Scholar
  43. Kareiva P (1989) Renewing the dialogue between theory and experiments in population ecology. In: Roughgarden J, May RM, Levin SA (eds) Perspectives in ecological theory. Princeton Univ Press, Princeton, pp 68–88Google Scholar
  44. Madden LV (1980) Quantification of disease progression. Prot Ecol 2: 159–176Google Scholar
  45. Madden LV (1986) Statistical analysis and comparison of disease progress curves. In: Leonard KJ, Fry WE (eds) Plant disease epidemiology: population dynamics and management, vol I. Macmillan, New York, pp 55–84Google Scholar
  46. Madden LV, Campbell CL (1990) Nonlinear disease progress curves. In: Kranz J (ed) Epidemics of plant disease: mathematical modelling and analysis, 2nd edn. Springer, Berlin Heidelberg New York, pp 181–229Google Scholar
  47. Martin SB, Hoch HC, Abawi GS (1983) Population dynamics of Laetisaeria arvalis and low-temperature Pythium spp. in untreated and pasteurized beet field soils. Phytopathology 73: 1445–1449CrossRefGoogle Scholar
  48. May RM (1974) Stability and complexity in model ecosystems. Princeton Univ Press, PrincetonGoogle Scholar
  49. May RM (1981) Models for two interacting populations. In: May RM (ed) Theoretical ecology: principles and applications. 2nd edn. Blackwell, Oxford, pp 78–104Google Scholar
  50. Neter J, Wasserman W (1974) Applied linear statistical models. Richard D Urwin, Homewood, ILGoogle Scholar
  51. Reynolds KM, Gold HJ, Bruck RI, Benson DM, Campbell CL (1986) Simulation of the spread of Phytophthora cinnamomi causing a root rot of Fraser fir in nursery beds. Phytopathology 76: 1190–1201CrossRefGoogle Scholar
  52. Ross GJS (1990) Nonlinear estimation. Springer, Berlin Heidelberg New YorkCrossRefGoogle Scholar
  53. Sanders FE, Sheikh NA (1983) The development of vesicular-arbuscular mycorrhizal infection in plant root systems. Plant Soil 71: 223–246CrossRefGoogle Scholar
  54. Scott PR (1969) Control of survival of Ophiobolus graminis between consecutive crops of winter wheat. Ann Appl Biol 63: 37–43CrossRefGoogle Scholar
  55. Skou JP (1975) Studies on the take-all fungus, Gaeumannomyces graminis. IV. Development and regeneration of roots in cereal species during the attack. K Vet Landbohojsk Arsskr 1975: 142–160Google Scholar
  56. Slope DB, Cox J (1964) Continuous wheat growing and the decline of take-all. Rothamsted Experimental Report for 1963, Rothamsted Experiment Station, Rothamsted, pp 108–115Google Scholar
  57. Toussoun TA (1975) Fwsanwra-suppressive soils. In: Bruehl GW (ed) Biology and control of soilborne plant pathogens. Am Phytopathol Soc, St Paul, Minnesota, pp 145–151Google Scholar
  58. Turner ME, Bradley EL, Kirk KA (1976) A theory of growth. Math Biosci 29: 367–373CrossRefGoogle Scholar
  59. Van der Plank JE (1963) Plant diseases: epidemics and control. Academic Press, New YorkGoogle Scholar
  60. Waggoner PE (1986) Progress curves of foliar diseases: their interpretation and use. In: Leonard KJ, Fry WE (eds) Plant disease epidemiology: population dynamics and management, vol I. Macmillan, New York, pp 3–37Google Scholar
  61. Washington WS (1988) Phytophthora cryptogea as a cause of root rot of raspberry in Australia; resistance of raspberry cultivars and control by fungicides. Plant Pathol 37: 225–230CrossRefGoogle Scholar
  62. Werker AR, Gilligan CA (1990) Analysis of the effects of selected agronomic factors on the epidemiology of the take-all fungus. Plant Pathol 39: 161–177CrossRefGoogle Scholar
  63. Werker AR, Gilligan CA, Hornby D (1991) Analysis of disease progress curves for take-ali in consecutive crops of winter wheat. Plant Pathol 40: 8–24CrossRefGoogle Scholar

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© Springer-Verlag Berlin Heidelberg 1994

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  • C. A. Gilligan

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