Big-data approaches lead to an increased understanding of the ecology of animal movement
Nathan R, Monk CT, Arlinghaus R, Adam T, Alos J, Assaf M, Baktoft H, Beardsworth CE, Bertram MG, Bijleveld AI, Brodin T, et al. (2022)
Science 375(6582): eabg1780.
Zeitschriftenaufsatz
| Veröffentlicht | Englisch
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Autor*in
Nathan, Ran;
Monk, Christopher T;
Arlinghaus, Robert;
Adam, TimoUniBi;
Alos, Josep;
Assaf, Michael;
Baktoft, Henrik;
Beardsworth, Christine E;
Bertram, Michael G;
Bijleveld, Allert I;
Brodin, Tomas;
Brooks, Jill L
Alle
Alle
Abstract / Bemerkung
Understanding animal movement is essential to elucidate how animals interact, survive, and thrive in a changing world. Recent technological advances in data collection and management have transformed our understanding of animal "movement ecology" (the integrated study of organismal movement), creating a big-data discipline that benefits from rapid, cost-effective generation of large amounts of data on movements of animals in the wild. These high-throughput wildlife tracking systems now allow more thorough investigation of variation among individuals and species across space and time, the nature of biological interactions, and behavioral responses to the environment. Movement ecology is rapidly expanding scientific frontiers through large interdisciplinary and collaborative frameworks, providing improved opportunities for conservation and insights into the movements of wild animals, and their causes and consequences.
Erscheinungsjahr
2022
Zeitschriftentitel
Science
Band
375
Ausgabe
6582
Art.-Nr.
eabg1780
eISSN
1095-9203
Page URI
https://pub.uni-bielefeld.de/record/2961460
Zitieren
Nathan R, Monk CT, Arlinghaus R, et al. Big-data approaches lead to an increased understanding of the ecology of animal movement. Science. 2022;375(6582): eabg1780.
Nathan, R., Monk, C. T., Arlinghaus, R., Adam, T., Alos, J., Assaf, M., Baktoft, H., et al. (2022). Big-data approaches lead to an increased understanding of the ecology of animal movement. Science, 375(6582), eabg1780. https://doi.org/10.1126/science.abg1780
Nathan, Ran, Monk, Christopher T, Arlinghaus, Robert, Adam, Timo, Alos, Josep, Assaf, Michael, Baktoft, Henrik, et al. 2022. “Big-data approaches lead to an increased understanding of the ecology of animal movement”. Science 375 (6582): eabg1780.
Nathan, R., Monk, C. T., Arlinghaus, R., Adam, T., Alos, J., Assaf, M., Baktoft, H., Beardsworth, C. E., Bertram, M. G., Bijleveld, A. I., et al. (2022). Big-data approaches lead to an increased understanding of the ecology of animal movement. Science 375:eabg1780.
Nathan, R., et al., 2022. Big-data approaches lead to an increased understanding of the ecology of animal movement. Science, 375(6582): eabg1780.
R. Nathan, et al., “Big-data approaches lead to an increased understanding of the ecology of animal movement”, Science, vol. 375, 2022, : eabg1780.
Nathan, R., Monk, C.T., Arlinghaus, R., Adam, T., Alos, J., Assaf, M., Baktoft, H., Beardsworth, C.E., Bertram, M.G., Bijleveld, A.I., Brodin, T., Brooks, J.L., Campos-Candela, A., Cooke, S.J., Gjelland, K.O., Gupte, P.R., Harel, R., Hellstrom, G., Jeltsch, F., Killen, S.S., Klefoth, T., Langrock, R., Lennox, R.J., Lourie, E., Madden, J.R., Orchan, Y., Pauwels, I.S., Riha, M., Roeleke, M., Schlagel, U.E., Shohami, D., Signer, J., Toledo, S., Vilk, O., Westrelin, S., Whiteside, M.A., Jaric, I.: Big-data approaches lead to an increased understanding of the ecology of animal movement. Science. 375, : eabg1780 (2022).
Nathan, Ran, Monk, Christopher T, Arlinghaus, Robert, Adam, Timo, Alos, Josep, Assaf, Michael, Baktoft, Henrik, Beardsworth, Christine E, Bertram, Michael G, Bijleveld, Allert I, Brodin, Tomas, Brooks, Jill L, Campos-Candela, Andrea, Cooke, Steven J, Gjelland, Karl O, Gupte, Pratik R, Harel, Roi, Hellstrom, Gustav, Jeltsch, Florian, Killen, Shaun S, Klefoth, Thomas, Langrock, Roland, Lennox, Robert J, Lourie, Emmanuel, Madden, Joah R, Orchan, Yotam, Pauwels, Ine S, Riha, Milan, Roeleke, Manuel, Schlagel, Ulrike E, Shohami, David, Signer, Johannes, Toledo, Sivan, Vilk, Ohad, Westrelin, Samuel, Whiteside, Mark A, and Jaric, Ivan. “Big-data approaches lead to an increased understanding of the ecology of animal movement”. Science 375.6582 (2022): eabg1780.
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