Th-116-1
Standardized Sampling: A Call for Gear Calibration

James T. Peterson , Department of Fisheries and Wildlife, Oregon State University, USGS Oregon Cooperative Fish and Wildlife Research Unit, Corvallis, OR
Craig P. Paukert , School of Natural Resources, USGS Missouri Cooperative Fish and Wildlife Research Unit, Columbia, MO
Amanda Rosenberger , School of Natural Resources, U.S. Geological Survey Missouri Cooperative Fish and Wildlife Research Unit, University of Missouri, Columbia, MO
Shannon K. Brewer , U.S. Geological Survey, Oklahoma Cooperative Fish and Wildlife Research Unit, Stillwater, OK
The recent movement toward adopting standardized methods for sampling fishes may improve fisheries management and our understanding of fish population dynamics. Standardization, however, does not necessarily alleviate sampling biases. The ability to capture fishes is influenced by species, body size, and habitat. Because these factors are linked to fish population dynamics, evaluations of spatial and temporal trends in fish sample data may reveal false trends. Fishery biologists can minimize the potential effects of sample biases by evaluating sampling efficiency, which is often achieved by gear calibration. Such evaluations, however, are uncommon or unpublished. A systematic literature review suggested that most studies are simple gear comparisons and few focused on calibration; a mere 7% were focused on warmwater stream sampling. Estimated sampling efficiency can be used to adjust fish sample data to obtain unbiased or minimally biased estimates of fish abundance and presence, including confidence limits, and facilitate comparisons among methods. The widespread adoption of standardized methods provides an opportunity for fishery biologists to pool resources and develop an improved understanding and estimates of fish sampling efficiency. We describe alternative gear calibration techniques, provide estimates of sampling efficiency for several sampling techniques, and highlight the techniques with insufficient gear efficiency information.