Estimating Taylor's power law parameters for weeds and the effect of spatial scale

The spatial variability of weeds within fields was studied for six sets of count data. Heterogeneity for a given mean population density was measured using the variance of the counts between sample units at different locations; relatively large values of sample variance imply aggregation. The dependence of variance on mean was measured using the relationship known as Taylor's power law, ubiquitous in animal ecology but seldom used for plant populations. This was fitted to an extensive set of plant counts and 69 estimates of its parameters b, an index of aggregation, and log(10)a were computed. Estimates were corrected for bias when the number of samples was small. Overall, b varied between 1.32 and 2.61, and log(10)a varied between -0.85 and 1.58, agreeing well with previous estimates for both plant and animal populations. Parameter estimates varied with sample size and spatial sample scale, but unpredictably. Parameter values when species counts were combined were compared with individual species analyses. Knowledge of the likely range of these parameters for weed populations provides an important basis for future modelling of the relationship between weed density and crop yield loss.