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Effect of imperfect detectability on adaptive and conventional sampling: Simulated sampling of freshwater mussels in the upper Mississippi River

Environmental Monitoring and Assessment

By:
, , , and
DOI: 10.1007/s10661-009-1251-8

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Abstract

Adaptive sampling designs are recommended where, as is typical with freshwater mussels, the outcome of interest is rare and clustered. However, the performance of adaptive designs has not been investigated when outcomes are not only rare and clustered but also imperfectly detected. We address this combination of challenges using data simulated to mimic properties of freshwater mussels from a reach of the upper Mississippi River. Simulations were conducted under a range of sample sizes and detection probabilities. Under perfect detection, efficiency of the adaptive sampling design increased relative to the conventional design as sample size increased and as density decreased. Also, the probability of sampling occupied habitat was four times higher for adaptive than conventional sampling of the lowest density population examined. However, imperfect detection resulted in substantial biases in sample means and variances under both adaptive sampling and conventional designs. The efficiency of adaptive sampling declined with decreasing detectability. Also, the probability of encountering an occupied unit during adaptive sampling, relative to conventional sampling declined with decreasing detectability. Thus, the potential gains in the application of adaptive sampling to rare and clustered populations relative to conventional sampling are reduced when detection is imperfect. The results highlight the need to increase or estimate detection to improve performance of conventional and adaptive sampling designs.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Effect of imperfect detectability on adaptive and conventional sampling: Simulated sampling of freshwater mussels in the upper Mississippi River
Series title:
Environmental Monitoring and Assessment
DOI:
10.1007/s10661-009-1251-8
Volume
170
Issue:
1-4
Year Published:
2010
Language:
English
Publisher:
Springer
Contributing office(s):
Leetown Science Center
Description:
9 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Environmental Monitoring and Assessment
First page:
499
Last page:
507
Other Geospatial:
Mississippi River