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Using variance components to estimate power in a hierarchically nested sampling design
Environmental Monitoring and Assessment
  • Maria Dzul, Iowa State University
  • Philip M. Dixon, Iowa State University
  • Michael C. Quist, Iowa State University
  • Stephen J Dinsmore, Iowa State University
  • Michael R. Bower, National Park Service
  • Kevin P. Wilson, National Park Service
  • D. Bailey Gaines, National Park Service
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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.

This is an article from Environmental Monitoring and Assessment 185 (2013): 405, doi:10.1007/s10661-012-2562-8. Posted with permission.

Works produced by employees of the U.S. Government as part of their official duties are not copyrighted within the U.S. The content of this document is not copyrighted.
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Maria Dzul, Philip M. Dixon, Michael C. Quist, Stephen J Dinsmore, et al.. "Using variance components to estimate power in a hierarchically nested sampling design" Environmental Monitoring and Assessment Vol. 185 Iss. 1 (2013) p. 405 - 414
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