Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river
Reliable estimates of abundance are needed to assess consequences of proposed habitat restoration and enhancement projects on freshwater mussels in the Upper Mississippi River (UMR). Although there is general guidance on sampling techniques for population assessment of freshwater mussels, the actual performance of sampling designs can depend critically on the population density and spatial distribution at the project site. To evaluate various sampling designs, we simulated sampling of populations, which varied in density and degree of spatial clustering. Because of logistics and costs of large river sampling and spatial clustering of freshwater mussels, we focused on adaptive and non-adaptive versions of single and two-stage sampling. The candidate designs performed similarly in terms of precision (CV) and probability of species detection for fixed sample size. Both CV and species detection were determined largely by density, spatial distribution and sample size. However, designs did differ in the rate that occupied quadrats were encountered. Occupied units had a higher probability of selection using adaptive designs than conventional designs. We used two measures of cost: sample size (i.e. number of quadrats) and distance travelled between the quadrats. Adaptive and two-stage designs tended to reduce distance between sampling units, and thus performed better when distance travelled was considered. Based on the comparisons, we provide general recommendations on the sampling designs for the freshwater mussels in the UMR, and presumably other large rivers.
Citation Information
Publication Year | 2011 |
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Title | Evaluation of single and two-stage adaptive sampling designs for estimation of density and abundance of freshwater mussels in a large river |
DOI | 10.1002/rra.1334 |
Authors | D. R. Smith, J. T. Rogala, B. R. Gray, S. J. Zigler, T.J. Newton |
Publication Type | Article |
Publication Subtype | Journal Article |
Series Title | River Research and Applications |
Index ID | 70034184 |
Record Source | USGS Publications Warehouse |
USGS Organization | Leetown Science Center |