An assessment of distance sampling techniques for estimating animal abundance

Abstract

Line transects have been widely applied for the estimation of animal abundance because they are regarded as simple, economical, and relatively precise. The recent development of automated techniques for the estimation of animal density from distance sampling data allows greater potential for field biologists and wildlife managers to become involved in the analytical summary of their research. An assessment was made of the ability of program DISTANCE to produce unbiased estimates of density in spite of potential sources of error from the estimation of transect and population density. Populations were simulated to investigate the robustness of program DISTANCE to changes in the density, distribution, and detection of animals across sampling areas and transects. It is concluded that if distance sampling data is collected reliably from a random sample of possible primary sampling units (PSUs) it can be expected that estimates of density will be presented accurately and with correct estimates of variance. If the proportion of the study area surveyed by transects is large however, then the presence of large between PSU variation will cause the variance estimates from program DISTANCE to be a sizeable overestimate.