Line-intercept laboratory subsampling estimates periphyton biovolumes more efficiently than standard methods.

Published online
11 Oct 2006
Content type
Journal article
Journal title
Journal of Applied Ecology
DOI
10.1111/j.1365-2664.2006.01205.x

Author(s)
Frappier, B. & Ducey, M. J.
Contact email(s)
Frappier@unh.edu

Publication language
English

Abstract

Algal assemblages have been included in biological monitoring in a number of national, large-scale and long-term biological monitoring and assessment programmes of streams, lakes and wetlands. However, there has been no substantial investigation of alternative enumeration strategies. We compared the sampling efficiency of the common periphyton subsampling strategies of counting 300 cells by strip counts or random fields and measuring 10 cells per taxon for biovolume, with line-intercept sampling (LIS), using samples collected from four streams differing in canopy cover and discharge. We also simulated the optimum ratio of cells tallied to cells measured for biovolume for all approaches. LIS was 1.6-5.5 times more efficient at estimating algal taxa biovolume than the 300-cell count methods. LIS performed best relative to conventional 300-cell count methods in streams with high biovolume, although efficiency gains were still noticeable in low biovolume streams. In addition, LIS tended to detect more taxa than the conventional 300-cell target biological assessment methods. In simulations, LIS was more efficient than the conventional methods for nearly all combinations of target cell count and cells measured for biovolume. No single optimal ratio of cells counted to cells measured was found. The target cell count that resulted in the greatest efficiency was higher in assemblages with large variation in cell density. Likewise, assemblages with high variance in taxa biovolume were most efficiently sampled by measuring more cells. Synthesis and applications. An increase in sampling efficiency as a result of greater adoption of LIS sampling may result in more accurate estimation of the relationships between periphyton community composition and environmental factors, and more sensitive detection of impacts using stream periphyton. Additionally, LIS may improve estimates in other ecological research fields employing microscopic counting chambers.

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