Abstract
This chapter describes how each of the sampling units is assessed to obtain either the actual abundance or an estimate of the abundance on each sampling unit. It discusses complete counts (censuses), indices, and enumeration methods that adjust for incomplete detectability of individuals. Efficient population estimators are needed to minimize the variance of the estimated population size of each sampling unit. Inefficient estimators will result in high sampling variation because there is a lot of noise associated with each sampling unit. That is, the population estimates all have large standard errors, and as a result, the variation among sampling units is large. The enumeration variance contributes to the overall variance of the survey, so the aim is to keep the enumeration variance as small as possible. Methods for assessing the numbers of individuals within a sampling unit can be categorized as complete and partial counts. Complete counts are a complete enumeration (census) of individuals within a sampling unit. Thus, a random sample of quadrats might be drawn, and all the individuals counted on each of the quadrats. Such counts are rarely possible in studies of animal populations.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
