Empirically simulated study to compare and validate sampling methods used in aerial surveys of wildlife populations

This paper compares the distribution. sampling and estimation of abundance for two animal species in an African ecosystem by means of an intensive sim ulation of the sampling process under a geographical information system (GI S) environment. It focuses on systematic and random sampling designs, commo nly used in wild-life surveys, comparing their performance to an adaptive d esign at three increasing sampling intensities, using the root mean square errors (RMSE). It further assesses the impact of sampling designs and inten sities on estimates of population parameters. The simulation is based on da ta collected during a prior survey, in which geographical locations of all observed animals were recorded. This provides more detailed data than that usually available from transect surveys. The results show precision of esti mates to increase with increasing sampling intensity, while no significant differences are observed between estimates obtained under random and system atic designs. An increase in precision is observed for the adaptive design, thereby validating the use of this design for sampling clustered populatio ns. The study illustrates the benefits of combining statistical methods wit h GIS techniques to increase insight into wildlife population dynamics.