%D 2008
%0 MEDLINE
%T A comparison of plotless density estimators using Monte Carlo simulation on totally enumerated field data sets .
%J BMC Ecol
%V 8
%P 6
%A White NA
%A Engeman RM
%A Sugihara RT
%A Krupa HW
%M pub18416853
%X 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 , eg 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 .