Dispersion of arthropods, flower buds and fruit in cotton fields: effects of population density and season on the fit of probability distributions

Three years data on insects and plant parts gathered using 3 sample methods (visual whole plant field observations, removal of plants in bags, sweepnet) were examined to determine the influence of several factors on the ‘fit ’ of 8 discrete probability distributions. To enable ‘fits ’ to he tested, critical values of the Kolmogorov-Smirnov statistic for use with discretedistributions wereobtained by Monte Carlo simulation. For data from a11 3 sample methods most distributions gave worse fits as population density increased. Better fits were obtained early in the growing season but the effect was small. The Negative Binomial appeared to be the most robust model on which to base simultaneous sampling of plant parts and several species of arthropods because it was least sensitive to effects of population density. In data collected by sweep sampling, clumping was less evident, and the Poisson and Poisson with Zeros gave the best fits at low densities when the data were uniformly distributed (variance less than mean) and the Negative Binomial at high densities when the distributions were clumped