A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets

Background: Plotless density estimators are those that are based on distance measures rather than counts per unit area (quadrats or plots) to estimate the density of some usually stationary event, e.g. burrow openings, damage to plant stems, etc. These estimators typically use distance measures between events and from random points to events to derive an estimate of density. The error and bias of these estimators for the various spatial patterns found in nature have been examined using simulated populations only. In this study we investigated eight plotless density estimators to determine which were robust across a wide range of data sets from fully mapped field sites. They covered a wide range of situations including animal damage to rice and corn, nest locations, active rodent burrows and distribution of plants. Monte Carlo simulations were applied to sample the data sets, and in all cases the error of the estimate (measured as relative root mean square error) was reduced with increasing sample size. The method of calculation and ease of use in the field were also used to judge the usefulness of the estimator. Estimators were evaluated in their original published forms, although the variable area transect (VAT) and ordered distance methods have been the subjects of optimization studies. Results: An estimator that was a compound of three basic distance estimators was found to be robust across all spatial patterns for sample sizes of 25 or greater. The same field methodology can be used either with the basic distance formula or the formula used with the Kendall-Moran estimator in which case a reduction in error may be gained for sample sizes less than 25, however, there is no improvement for larger sample sizes. The variable area transect (VAT) method performed moderately well, is easy to use in the field, and its calculations easy to undertake. Conclusion: Plotless density estimators can provide an estimate of density in situations where it would not be practical to layout a plot or quadrat and can in many cases reduce the workload in the field.

Absolute quantitation of Marek's disease virus and Herpesvirus of turkeys in chicken lymphocyte, feather tip and dust samples using real-time PCR

The further development of Taqman quantitative real-time PCR (qPCR) assays for the absolute quantitation of Marek's disease virus serotype 1 (MDV1) and Herpesvirus of turkeys (HVT) viruses is described and the sensitivity and reproducibility of each assay reported. Using plasmid DNA copies, the lower limit of detection was determined to be 5 copies for the MDV1 assay and 75 copies for the HVT assay. Both assays were found to be highly reproducible for Ct values and calculated copy numbers with mean intra- and inter-assay coefficients of variation being less than 5% for Ct and 20% for calculated copy number. The genome copy number of MDV1 and HVT viruses was quantified in PBL and feather tips from experimentally infected chickens, and field poultry dust samples. Parallelism was demonstrated between the plasmid-based standard curves, and standard curves derived from infected spleen material containing both viral and host DNA, allowing the latter to be used for absolute quantification. These methods should prove useful for the reliable differentiation and absolute quantitation of MDV1 and HVT viruses in a wide range of samples.