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Alden T. Tilley

Publications and source records attributed to Alden T. Tilley.

2 recordsLinked to original sources

Efficiency of down-looking cameras for detecting round goby (Neogobius melanostomus) over varying substrates in laboratory microcosms

Since invading the Laurentian Great Lakes in the late 1980s, round goby Neogobius melanostomus have become a dominant benthic prey species, resulting in a need to accurately monitor their population abundance to inform fisheries management. Camera-based methods for assessing round goby abundances have gained popularity, but their efficiencies for detecting round goby are poorly understood. We evaluated the efficiency of down-looking color monocular cameras for detecting round goby presence in microcosm enclosures with known numbers of fish. Detection efficiencies were compared between sand and cobble substrate during daylight hours using a generalized linear mixed-effects model. After accounting for trial effects, enclosure placement, and within-replicate temporal autocorrelation, round goby detection efficiency was 98.6% over sand (95% confidence limit (CL): 98.0–99.0%), and 55.3% over a single layer of cobble substrate (CL: 48.6–61.8%). The large difference in detectability between cobble and sand suggests that camera-based estimates of round goby abundances are likely to be biased low and have lower relative precision in high-structure habitats, but may be largely unbiased in low-structure habitats. Despite much lower relative detection efficiencies of cameras in high-structure cobble habitats, the efficiencies reported here still compare favorably to conventional methods like otter and beam trawling. Our results provide initial quantitative bounds on the possible degree of negative bias in camera-based estimates of round goby abundances in different substrates, but require further field verification across the diversity of substrates, interstitial infilling, and other structural attributes of habitat found in the Great Lakes.

Michigan↗

Design and function of the Autonomous Benthic Imaging and Surveying System (ABISS) for remote sensing of lake and seabed environments

Lake and seabed environments are home to fisheries and other biota that are important to ecosystems and economies, yet these environments and the species that use them are difficult to accurately assess and monitor. Traditional benthic survey techniques, like bottom trawling used by the U.S. Geological Survey, are limited by substrate constraints, poor spatial resolution and precision, and operational depth limits, hindering accurate assessment of benthic species and habitats. In response to these limitations, the U.S. Geological Survey developed the Autonomous Benthic Imaging and Surveying System, a camera system integrated into underwater vehicles, to capture high-resolution images of the lakebed. The system uses color and stereo cameras to collect imagery, which can be analyzed using computational methods to detect organisms and (or) characterize habitat features, such as geologic substrate types. The system has been integrated into autonomous underwater vehicles and into an underwater housing used by self-contained underwater breathing apparatus (SCUBA) divers. Although the engineering of the system was motivated by the need for data collection in the Great Lakes, it has potential to collect high quality data in any aqueous setting with sufficient water clarity and safe operating conditions. The Autonomous Benthic Imaging and Surveying System can operate across diverse depths and light conditions to map and quantify ecological patterns that were difficult or impossible to assess using traditional methods. The Autonomous Benthic Imaging and Surveying System offers the potential for accurate and precise monitoring and assessment of native benthic biota, invasive species, and habitat, potentially providing natural resource managers with improved information to support decision making about benthic resource management.

Great Lakes↗