Application of Balanced Acceptance Sampling to an Intertidal Survey

Naeimeh Abi; Mohammad Moradi; Mohammad Salehi; Jennifer Brown; Jassim A. Al-Khayat; Elena Moltchanova

doi:10.1515/jlecol-2017-0012

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Application of Balanced Acceptance Sampling to an Intertidal Survey

Journal of Landscape Ecology

Volume 10 (2017): Issue 1 (January 2017)

By: Naeimeh Abi, Mohammad Moradi, Mohammad Salehi, Jennifer Brown, Jassim A. Al-Khayat and Elena Moltchanova

Open Access

|Jul 2017

Abstract

In ecological studies, the population of interest is often spread over a large area. In these studies, obtaining a sample with good spatial coverage is an important feature in the design of a survey. In most cases adjacent, or neighbouring, units are more similar than units further apart and the resulting spatial autocorrelation should be taken into account.

Two dimensional systematic sampling (grid-based sampling) is one conventional method that has been used in environmental studies to achieve spatial coverage of the area.

Balanced Acceptance Sampling (BAS) is a new method for selecting well spread out sampling units over the study area.

In this paper we will compare the BAS design and two dimensional systematic sampling for selecting samples (quadrats) from a large area, using a case study of a crab species from an intertidal marine zone in Qatar.

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Articles in this issue

DOI: https://doi.org/10.1515/jlecol-2017-0012 | Journal eISSN: 1805-4196 | Journal ISSN: 1803-2427

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Language: English

Page range: 96 - 107

Submitted on: Mar 28, 2017

Accepted on: Jun 4, 2017

Published on: Jul 14, 2017

Published by: Czech Society for Landscape Ecology

In partnership with: Paradigm Publishing Services

Publication frequency: 4 issues per year

Keywords:

Two dimensional systematic sampling,

Balanced acceptance sampling,

Quadrat,

Crustacea,

Spatial autocorrelation

Related subjects:

© 2017 Naeimeh Abi, Mohammad Moradi, Mohammad Salehi, Jennifer Brown, Jassim A. Al-Khayat, Elena Moltchanova, published by Czech Society for Landscape Ecology
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Volume 10 (2017): Issue 1 (January 2017)