literature, ecological theory, and expert opinion. We demonstrate that, despite being frequently ranked the “best model …

Systematic sampling is easy, efficient, and widely used, though it is not generally recognized that a systematic sample … of them determine which estimators are unbiased, when using the sampling design as the basis for inference. We describe … selection. When the population size is known at the outset, systematic sampling with unrestricted selection is most likely the …

inventory of fine woody debris (FWD); however, the sampling protocols involve tallying only the number of FWD pieces by size … class that intersect a sampling transect with no measure of actual size. The line intersect estimator used with those …

Binomial sampling based on the proportion of samples infested was investigated for estimating mean densities of citrus … parameters adequately described a validation data set from a sampling plan consisting of 192 samples. Projections indicated the … fitted parameters would apply to sampling plans with as few as 48 samples, but reducing sample size resulted in an increase …

. Projections indicated that a sampling plan consisting of 10 trees and eight flush shoots per tree would provide density estimates … presence-absence sampling plan with a fixed precision level was developed and can be used to provide a quick estimation of D …

both simple random and cluster sampling. The BRR estimate of variance is the sum of variances and covariances of unit …-level kNN estimates in the area of interest. In Monte Carlo simulations of simple random and cluster sampling from seven … and Monte Carlo sampling variances was good both for population and for small-area totals. The modified BRR estimator is …

In many applications of line intersect sampling, transects consist of multiple, connected segments in a prescribed … illustrated and a consistent sampling protocol, applicable to populations composed of arbitrarily shaped elements, is proposed. It …

Carlo, Latin hypercube sampling with constrained Monte Carlo, and generalized likelihood uncertainty estimation), and …

user determine the optimal number and location of samples using defensible statistical sampling design methods and displays … summarizing the assumptions and parameter inputs is generated and can be included in a sampling and analysis plan. VSP features …