KM Myrvold

Every sampling method is imperfect. By tailoring the right method to each problem we stand to gain further insights into aquatic ecology. 

 

We employ underwater video and drone footage to study behavior, habitat use, and migration timing in a non-invasive manner.

 

We collaborate with NTNU (The Norwegian University of Science and Technology) to apply computer vision (neural network models) to process large quantities of video footage and automate species identification and enumeration.

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Publications:

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Holter, TH, J Museth and KM Myrvold. 2020. Evaluating a fishway reconstruction amidst fluctuating abundances. River Research and Applications 36:1748-1753

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Myrvold, KM and BK Dervo. 2020. Flight elevation and water clarity affect the utility of unmanned aerial vehicles in mapping stream substratum. Fisheries Management and Ecology 27:167-169

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Myrvold, KM, TH Holter, BJ Nordølum, EO Lavik, KA Haugen, TRT Kvalvaag, M Pedersen, J Museth, in review, Ecohydrology. Monitoring fish assemblages in seasonal off-channel habitats using underwater video and computer vision.