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Using variance components to estimate power in a hierarchically nested sampling design improving monitoring of larval Devils Hole pupfish

Population Ecology

By:
, , , , , , and
DOI: 10.1007/s10661-012-2562-8

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Abstract

We used variance components to assess allocation of sampling effort in a hierarchically nested sampling design for ongoing monitoring of early life history stages of the federally endangered Devils Hole pupfish (DHP) (Cyprinodon diabolis). Sampling design for larval DHP included surveys (5 days each spring 2007–2009), events, and plots. Each survey was comprised of three counting events, where DHP larvae on nine plots were counted plot by plot. Statistical analysis of larval abundance included three components: (1) evaluation of power from various sample size combinations, (2) comparison of power in fixed and random plot designs, and (3) assessment of yearly differences in the power of the survey. Results indicated that increasing the sample size at the lowest level of sampling represented the most realistic option to increase the survey's power, fixed plot designs had greater power than random plot designs, and the power of the larval survey varied by year. This study provides an example of how monitoring efforts may benefit from coupling variance components estimation with power analysis to assess sampling design.

Additional Publication Details

Publication type:
Article
Publication Subtype:
Journal Article
Title:
Using variance components to estimate power in a hierarchically nested sampling design improving monitoring of larval Devils Hole pupfish
Series title:
Population Ecology
DOI:
10.1007/s10661-012-2562-8
Volume
185
Issue:
1
Year Published:
2013
Language:
English
Publisher:
Springer
Publisher location:
Amsterdam, Netherlands
Contributing office(s):
Idaho Cooperative Fish and Wildlife Research Unit
Description:
10 p.
Larger Work Type:
Article
Larger Work Subtype:
Journal Article
Larger Work Title:
Population Ecology
First page:
405
Last page:
414
Country:
United States
State:
California
Other Geospatial:
Devils Hole;Death Valley