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The effect of sample duration on the quantification of stream drift
Author(s) -
CULP JOSEPH M.,
SCRIMGEOUR GARRY J.,
BEERS CHRIS E.
Publication year - 1994
Publication title -
freshwater biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.297
H-Index - 156
eISSN - 1365-2427
pISSN - 0046-5070
DOI - 10.1111/j.1365-2427.1994.tb00850.x
Subject(s) - sample (material) , statistics , coefficient of variation , sample size determination , mathematics , duration (music) , sample variance , standard deviation , variance (accounting) , environmental science , chemistry , physics , accounting , chromatography , acoustics , business
SUMMARY 1. We performed computer simulations and a field experiment to determine the effect that sample duration and, thus, sample volume had on estimates of drift density and sample variance. 2. In computer simulations, when the spatial arrangement of individuals in the water column approximated a random and a contagious‐random distribution, estimated mean drift density was not significantly affected by sample duration, but sample variance decreased curvilinearly as sample duration increased. 3. Similar results were obtained in field experiments in habitats of high and low water velocity. 4. Our findings from an Albertan stream indicate that the relationship between sample variance (i.e. coefficient of variation) and duration of drift samples is curvilinear. This relationship affected the number of samples required to achieve a specific level of precision (i.e. a standard error within 10% of the mean). For estimates in low and high current velocities, sample variation was halved by increasing the duration of sample collections from 10 to 20 min. The increased precision obtained with samples of 20 min duration reduced the amount of drift material that needed to be processed by approximately 50% compared with an equivalent 10% level of precision for samples of 10 min duration. This reduction in the number of samples required to obtain a given level of precision has important consequences to the cost of processing drift samples. 5. Thus to optimize studies of stream invertebrate drift, both in terms of sample precision and processing effort, researchers must consider the effect that sample volume has on the variance of drift density estimates. Because researchers generally use drift nets with similar‐sized apertures (>300cm 2 ), the problem for specific field applications becomes one of optimizing sample duration relative to variance estimates for drift density.