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High-resolution, non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems

High-resolution, non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems

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FRANCISCO, Fritz A., Paul NÜHRENBERG, Alex JORDAN, 2020. High-resolution, non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems. In: Movement Ecology. BioMed Central. 8, 27. eISSN 2051-3933. Available under: doi: 10.1186/s40462-020-00214-w

@article{Francisco2020Highr-50032, title={High-resolution, non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems}, year={2020}, doi={10.1186/s40462-020-00214-w}, volume={8}, journal={Movement Ecology}, author={Francisco, Fritz A. and Nührenberg, Paul and Jordan, Alex}, note={Article Number: 27} }

Francisco, Fritz A. Attribution 4.0 International 2020 High-resolution, non-invasive animal tracking and reconstruction of local environment in aquatic ecosystems Nührenberg, Paul Jordan, Alex Jordan, Alex 2020-06-29T11:16:46Z Nührenberg, Paul 2020-06-29T11:16:46Z Background<br />Acquiring high resolution quantitative behavioural data underwater often involves installation of costly infrastructure, or capture and manipulation of animals. Aquatic movement ecology can therefore be limited in taxonomic range and ecological coverage.<br /><br />Methods<br />Here we present a novel deep-learning based, multi-individual tracking approach, which incorporates Structure-from-Motion in order to determine the 3D location, body position and the visual environment of every recorded individual. The application is based on low-cost cameras and does not require the animals to be confined, manipulated, or handled in any way.<br /><br />Results<br />Using this approach, single individuals, small heterospecific groups and schools of fish were tracked in freshwater and marine environments of varying complexity. Positional tracking errors as low as 1.09 ± 0.47 cm (RSME) in underwater areas up to 500 m2 were recorded.<br /><br />Conclusions<br />This cost-effective and open-source framework allows the analysis of animal behaviour in aquatic systems at an unprecedented resolution. Implementing this versatile approach, quantitative behavioural analysis can be employed in a wide range of natural contexts, vastly expanding our potential for examining non-model systems and species. Francisco, Fritz A. eng

Dateiabrufe seit 29.06.2020 (Informationen über die Zugriffsstatistik)

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