The sensitivity of the ordinary runs test for evaluating the spatial pattern of infected plants

Authors

  • Eduardo V. Trumper Sección Entomología, Estación Experimental Agropecuaria Manfredi, INTA, Ruta Nacional 9 Km 636, (5988) Manfredi, Córdoba, Argentina.
  • David E. Gorla Laboratorio de Ecología de Insectos, Facultad de Ciencias Agropecuarias, U.N.C., Avda. Valparaíso s/n (Campo Experimental), (5000) Córdoba, Argentina.

Abstract

The influence of disease incidence, clumping of infected plants, and size of the sampling unit on the sensitivity of the ordinary runs test was simulated in order to identify the optimum sampling profile for investigating the spatial pattern of plant diseases. A simulation programme was written to generate plant populations with random and clustered spatial patterns displayed in quadrats of 50 by 200 plants. 600 and 1200 independent populations were generated for random and clustered patterns, respectively. 12 levels of disease incidence were simulated within the range 0.01-0.95. For every population, the simulation performed a sampling procedure with 9 sizes of the sampling unit (20, 30, 40, 50, 60, 80, 100, 120 and 150 plants). In each case the simulation was based on 1000 samples of continuous series of plants. In order to evaluate the sensitivity of ordinary runs test to the degree of aggregation, plant populations were simulated with two additional values of clumping power, for two levels of disease incidence. When a random pattern was simulated, the probability of rejecting the null hypothesis was almost unaffected by the size of the sampling unit and slightly decreased with disease incidence. When clustered patterns were generated, the probability of error clearly decreased both with disease incidence and size of the sampling unit. The probability of error was also affected by the degree of aggregation. As expected, the higher the clumping power the higher the probability of rejecting the null hypothesis. The implications of the sensitivity of the runs test on the design of sampling schemes are discussed.

References

Campbell, C.L., W.R. Jacobi, N.T. Powell and C.E. Main. 1984. Analysis of disease progression and the randomness of occurrence ofinfected plants during tobacco black shank epidemics. Phytopathology 74:230-235.

Campbell,C.L. and L.V. Madden. 1990.Introduction to plant disease epidemiology. John Wiley & Sons. New York. 532 pp.

Madden, L.V. 1988. Dynamic nature of within-field disease and pathogen distributions. In: Jeger, M.J. (Ed.), The Spatial Component of Plant Disease Epidemics. Prentice Hall, Inc., New Jersey. pp. 96-126.

Madden, L.V. and C.L. Campbell. 1986. Descriptions of virus disease epidemics in time and space. In: Mc Lean, G.D., R.G. Garret and W.G. Ruesink (Eds.), Plant Virus Epidemics. Monitoring, Modelling and Predicting Outbreaks. Academic Press, Sydney. pp. 273-293.

Madden, L.V., R. Louie, J.J. AN and J.K. Knoke. 1982. Evaluation of testsfor randomness of infected plants. Phytopathology 72:195-198.

Madden, L.V., T.P. Pirone and B. Raccah. 1987a. Analysis ofspatial patterns of virus-diseased tobacco plants. Phytopathology 77:1409-1417.

Madden, L.V., T.P. Pirone and B. Raccah. 1987b. Temporal analysis of two viruses increasing in the same tobacco fields. Phytopathology 77:974-980.

Madden, L.V., K.M. Reynolds, T.P. Pirone and B. Raccah. 1988. Modeling of tobacco virus epidemics as spatio-temporal autoregressive integrated moving-average processes. Phytopathology 78:1361-1366.

Madden, L.V., J.K. Knoke and R. Louie. 1990. Spread of Maize Chlorotic Dwarf Virus in maize fields by its leathopper vector, Graminella nigrifrons. Phytopathology 80:291-298.

Reynolds, K.M. and L.V. Madden. 1988. Analysis of epidemics using spatio-temporal autocorrelation. Phytopathology 78:240-246.

Reynolds, K.M., L.V. Madden and M.A. Ellis. 1988. Spatio-temporal analysis of epidemics development of leather rot of strawberry. Phytopathology 78:246-252.

Southwood, T.R. 1978. Ecological Methods. With particular reference to insects. John Wiley & Sons, New York. 524 pp.

Taylor, L.R. 1984. Assesing and interpreting the spatial distribution of insect populations. Annual Review of Entomology 29:321-357.

Trumper, E.V., D.E. Gorla and M.P. Grilli. 1996. Spatial pattern of Rio Cuarto Corn Disease (“Mal de Rio Cuarto”) in corn fields. Ecologia Austral 6:131-136.

van der Werf, W., W.A.H. Rossing, R. Rabbinge, M.D. De Jong andP.J. Mols. 1989. Approachesto modelling the spatial dynamics of pests and diseases. In: Cavalloro, R. and V. Delucchi (Eds.). Proceedings of the Parasitis 88 Congress, 1988. Barcelona: Boletin de Sanidad Vegetal, Fuera de serie, No. 17. pp. 89-119.

van der Werf, W. and W. Riesebos. 1990. Modelsin the epidemiology of beet yellowing viruses. In: Proceedings of 53rd Winter Congress. Bruxelles: International Institute for Sugar Beet Research. pp. 333-353.

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Published

1997-12-01

How to Cite

Trumper, E. V., & Gorla, D. E. (1997). The sensitivity of the ordinary runs test for evaluating the spatial pattern of infected plants. Ecología Austral, 7(2), 079–086. Retrieved from https://ojs.ecologiaaustral.com.ar/index.php/Ecologia_Austral/article/view/1641

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