Random versus stratified location of transects or points in distance sampling: theoretical results and practical considerations
- 501 Downloads
A composite approach mixing design-based and model-based inference is considered for analyzing line-transect or point-transect data. In this setting, the properties of the animal abundance estimator stem from the sampling scheme adopted to locate transects or points on the study region, as well as from the modeled detection probabilities. Moreover, the abundance estimation can be viewed as a “generalized” version of Monte Carlo integration. This approach permits to prove the superiority of the stratified placement of transects or points (based on a regular tessellation of the study region) over the uniform random placement. Even if the result was already established for the fixed-area sampling, i.e., when a perfect detection takes place, it was lacking in distance sampling. Comparisons with other widely-applied schemes pursuing an even placement of transects or points are also considered.
KeywordsComposite approach Coverage probability Detection probability Monte Carlo integration Tessellation stratified sampling Uniform random sampling
Unable to display preview. Download preview PDF.
- Baddeley A, Jensen EBV (2005) Stereology for statisticians. Monographs on Statistics and Applied Probability, vol 103. Chapman and Hall/CRC, Boca RatonGoogle Scholar
- Barabesi L, Marcheselli M (2003) A modified Monte Carlo integration. Int Math J 3: 555–565Google Scholar
- Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2001) Introduction to distance sampling. Oxford University Press, OxfordGoogle Scholar
- Buckland ST, Anderson DR, Burnham KP, Laake JL, Borchers DL, Thomas L (2004) Advanced distance sampling. Oxford University Press, OxfordGoogle Scholar
- Burnham KP, AndersonDR Laake JL (1980) Estimation of density from line transect sampling of biological populations. Wildl Monogr 72: 1–203Google Scholar
- Gibbons DW, Gregory RD (2006) Birds. In: Sutherland WJ (ed) Ecological census techniques. Cambridge University Press, Cambridge, pp 227–255Google Scholar
- Gregoire TG, Valentine HT (2008) Sampling strategies for natural resources and the environment. Chapman & Hall/CRC, Boca RatonGoogle Scholar
- Leopold A (1933) Game management. Charles Scribner’s Sons, New York (reprinted in 1986 by University of Wisconsin Press, Madison)Google Scholar
- Thompson SK (2002) Sampling, 2nd edn. Wiley, New YorkGoogle Scholar