Confidence limits are a derivative of these standard measures of variability. They delineate an upper and lower limit around an estimate and provide a probability that the true value is contained within this range. As variability increases, it widens the confidence intervals at a given probability and erodes the confidence with which population parameters may be estimated. With specific regard to wildlife inventory, the greatest problem with sampling wildlife populations is the high degree of variation that can exist, even with repetitive sampling of the same population. When the variation between samples is high, the precision of the total estimated population parameter is low and consequently confidence limits are wide.
Most statistical procedures require that certain assumptions are met during the sampling procedure.
In the case of comparing changes in abundance between Study Areas, high variation makes it difficult to determine if there are statistically significant trends in the population. Therefore, it is important to carefully choose sampling techniques and develop sampling programs that both meet the necessary assumptions and minimize the variation between samples. It is also important to give careful consideration to the species and age classes of concern prior to the start of any sampling, as these may produce variability within the population being sampled. This may be anticipated and mitigated by having a basic understanding of the life history, habitat requirements and behaviour of the species that is under survey. The variability in the number and composition of species enumerated between Study Areas or at the same Study Area but at different times can naturally be very high even when the total population in the Project Area remains constant.