Abstract
AbstractThe use of diversity indices is adopted in surveys on biological population to quantify species diversity. However, when the population is clustered and spread in a very wide area, usual sampling designs provide estimators with large variances. In this case, if the study area is partitioned into a frame of sub‐areas, a suitable design is constituted by adaptive sampling. The adaptive sampling ensures that the abundance vector estimator is unbiased and more accurate than that obtained with simple random sampling. However, the corresponding diversity index estimator, which can be viewed as a function of the abundance vector estimator, is biased for finite samples. Accordingly, we propose the jackknife procedure in order to reduce the bias. Copyright © 2002 John Wiley & Sons, Ltd.
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