Effects of Prevailing Wind Direction on Spatial Statistics of Plant Disease Epidemics

A stochastic simulation model was used to study the e€ects of the strength of prevailing wind (W), the size/ shape (Q) of sampling quadrats and their orientation in relation to the prevailing wind direction (D) on spatial statistics describing plant diseases. Spore dispersal fol- lowed a half-Cauchy distribution with median dis- tance l, which depended on simulated wind speed. The relationship of spatial autocorrelation at distance k (qk) to disease incidence (p) and distance was well described by a four-parameter (a, b1, b2, b3) power-law model; at a given p, qk declined exponentially with distance. A total of 35 di€erent quadrat sizes, ranging from 4 to 432 plants, were used to sample the simulated epidemics for estimating intraclass correlation (j). The j-values decreased exponentially with increasing quad- rat size; a binary power law model with three parameters (a1, b4, b5) successfully related j to p. In general, the e€ect of W and D was greatest on the parameters a, b1, b2 and b3. The e€ect of W on a, b1, b2 and b3 depended critically on the spatial pattern of initial infected plants (Y); W had greatest e€ect for the random pattern. In contrast, the main e€ect of D and its interaction with W on the parameters a, b1, b2 and b3 were large and consistent over di€erent initial conditions. Variations in a1, b4 and b5 were predominantly due to Y and Q. Only for b5 under the clumped pattern was the e€ect of W very large. For the parameters a1, b4 and b5 there was a large interaction among W, Q and D for the clumped and regular patterns. As expected, in general, the e€ect of D increased with increasing prevailing wind strength, quadrat size and quadrat length : width ratio. Using square quadrats reduced signi®cantly the e€ect of W on the parameters a1, b4 and b5; however, the e€ect ofWon b5 was still very large for the clumped pattern. Sampling perpendicular to the prevailing wind direction generally resulted in larger di€erences in the nine estimated parameters.