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An adaptive two‐stage sequential design for sampling rare and clustered populations
Author(s) -
Brown Jennifer A.,
Salehi M. Mohammad,
Moradi Mohammad,
Bell Gavin,
Smith David R.
Publication year - 2008
Publication title -
population ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.819
H-Index - 59
eISSN - 1438-390X
pISSN - 1438-3896
DOI - 10.1007/s10144-008-0089-1
Subject(s) - sampling (signal processing) , adaptive sampling , sequential sampling , stage (stratigraphy) , sampling design , adaptive design , sample (material) , cluster sampling , multistage sampling , computer science , statistics , biology , mathematics , population , bioinformatics , monte carlo method , telecommunications , demography , paleontology , chemistry , chromatography , sociology , spatial distribution , clinical trial , detector
How to design an efficient large‐area survey continues to be an interesting question for ecologists. In sampling large areas, as is common in environmental studies, adaptive sampling can be efficient because it ensures survey effort is targeted to subareas of high interest. In two‐stage sampling, higher density primary sample units are usually of more interest than lower density primary units when populations are rare and clustered. Two‐stage sequential sampling has been suggested as a method for allocating second stage sample effort among primary units. Here, we suggest a modification: adaptive two‐stage sequential sampling. In this method, the adaptive part of the allocation process means the design is more flexible in how much extra effort can be directed to higher‐abundance primary units. We discuss how best to design an adaptive two‐stage sequential sample.