Gerlach G, Atema J, Kingsford MJ, Black KP, Miller-Sims V. Smelling home can prevent dispersal of reef fish larvae. Proc Natl Acad Sci. 2007; 104(3):858–63.
CAS
PubMed
Google Scholar
Somveille M, Manica A, Rodrigues AS. Where the wild birds go: explaining the differences in migratory destinations across terrestrial bird species. Ecography. 2018. https://doi.org/10.1111/ecog.03531.
Carr A, Carr MH. Site fixity in the caribbean green turtle. Ecology. 1972; 53(3):425–9.
Google Scholar
Strandburg-Peshkin A, Farine DR, Crofoot MC, Couzin ID. Habitat and social factors shape individual decisions and emergent group structure during baboon collective movement. eLife. 2017; 6:19505.
Google Scholar
Nagy M, Couzin ID, Fiedler W, Wikelski M, Flack A. Synchronization, coordination and collective sensing during thermalling flight of freely migrating white storks. Phil Trans R Soc B. 2018; 373(1746):20170011.
PubMed
Google Scholar
Cooke SJ. Biotelemetry and biologging in endangered species research and animal conservation: relevance to regional, national, and iucn red list threat assessments. Endanger Spec Res. 2008; 4(1-2):165–85.
Google Scholar
Costa DP, Breed GA, Robinson PW. New insights into pelagic migrations: implications for ecology and conservation. Ann Rev Ecol Evol Syst. 2012; 43:73–96.
Google Scholar
Runge CA, Watson JE, Butchart SH, Hanson JO, Possingham HP, Fuller RA. Protected areas and global conservation of migratory birds. Science. 2015; 350(6265):1255–8.
CAS
PubMed
Google Scholar
Lewison R, Hobday AJ, Maxwell S, Hazen E, Hartog JR, Dunn DC, Briscoe D, Fossette S, O’keefe CE, Barnes M, et al.Dynamic ocean management: identifying the critical ingredients of dynamic approaches to ocean resource management. BioScience. 2015; 65(5):486–98.
Google Scholar
Thys TM, Ryan JP, Dewar H, Perle CR, Lyons K, O’Sullivan J, Farwell C, Howard MJ, Weng KC, Lavaniegos BE, Gaxiola-Castro G, Bojorquez LEM, Hazen EL, Bograd SJ. Ecology of the ocean sunfish, mola mola, in the southern california current system. J Exp Mar Biol Ecol. 2015; 471:64–76. https://doi.org/10.1016/j.jembe.2015.05.005.
Google Scholar
Hussey NE, Kessel ST, Aarestrup K, Cooke SJ, Cowley PD, Fisk AT, Harcourt RG, Holland KN, Iverson SJ, Kocik JF, Mills Flemming JE, Whoriskey FG. Aquatic animal telemetry: A panoramic window into the underwater world. Science. 2015; 348(6240). https://doi.org/10.1126/science.1255642. https://science.sciencemag.org/content/sci/348/6240/1255642.full.pdf.
van Diggelen F, Enge P. The worlds first gps mooc and worldwide laboratory using smartphones. In: Proceedings of the 28th International Technical Meeting of The Satellite Division of the Institute of Navigation (ION GNSS+ 2015): 2015. p. 361–9.
Kays R, Crofoot MC, Jetz W, Wikelski M. Terrestrial animal tracking as an eye on life and planet. Science. 2015; 348(6240):2478.
Google Scholar
Andersen KH, Berge T, Gonçalves RJ, Hartvig M, Heuschele J, Hylander S, Jacobsen NS, Lindemann C, Martens EA, Neuheimer AB, et al.Characteristic sizes of life in the oceans, from bacteria to whales. Ann Rev Mar Sci. 2016; 8:217–41.
CAS
PubMed
Google Scholar
Krause J, Krause S, Arlinghaus R, Psorakis I, Roberts S, Rutz C. Reality mining of animal social systems. Trends Ecol Evol. 2013; 28(9):541–51.
PubMed
Google Scholar
Jepsen N, Koed A, Thorstad E, Baras E. Surgical implantation of telemetry transmitters in fish: How much have we learned?Hydrobiologia. 2002; 483:239–48. https://doi.org/10.1023/A:1021356302311.
Google Scholar
Bergé J, Capra H, Pella H, Steig T, Ovidio M, Bultel E, Lamouroux N. Probability of detection and positioning error of a hydro acoustic telemetry system in a fast-flowing river: intrinsic and environmental determinants. Fish Res. 2012; 125:1–13.
Google Scholar
James D, Fischer J, Laube J, Spindler M. An accuracy assessment of ultrasonic transmitter locations determined by mobile telemetry in aquatic systems. Fish Manag Ecol. 2014; 21(5):421–5.
Google Scholar
Mora C, Tittensor DP, Adl S, Simpson AG, Worm B. How many species are there on earth and in the ocean?PLoS Biol. 2011; 9(8):1001127.
Google Scholar
Hawaii Pacific University Oceanic Institute Aqua Facts. https://www.oceanicinstitute.org/aboutoceans/aquafacts.html. Accessed 24 Jan 2019.
National Oceanic and Atmospheric Administration Oceans & Coasts. https://www.noaa.gov/oceans-coasts. Accessed 24 Jan 2019.
Ray GC. Coastal-zone biodiversity patterns. Bioscience. 1991; 41(7):490–8.
Google Scholar
Food and Agriculture Organization of the United Nations. The state of food and agriculture 1991. 1992. https://doi.org/10.18356/e3f71a7b-en.
Clark JR. Coastal zone management for the new century. Ocean Coast Manag. 1997; 37(2):191–216. https://doi.org/10.1016/S0964-5691(97)00052-5. Lessons Learned in Integrated Coastal Management.
Google Scholar
do Sul JAI, Costa MF. The present and future of microplastic pollution in the marine environment. Environ Pollut. 2014; 185:352–64. https://doi.org/10.1016/j.envpol.2013.10.036.
Google Scholar
Chust G, Ángel Borja, Liria P, Galparsoro I, Marcos M, Caballero A, Castro R. Human impacts overwhelm the effects of sea-level rise on basque coastal habitats (n spain) between 1954 and 2004. Estuar Coast Shelf Sci. 2009; 84(4):453–62. https://doi.org/10.1016/j.ecss.2009.07.010.
Google Scholar
Friedlander AM. Marine conservation in oceania: Past, present, and future. Mar Pollut Bull. 2018; 135:139–49.
CAS
PubMed
Google Scholar
Berman GJ, Choi DM, Bialek W, Shaevitz JW. Mapping the structure of drosophilid behavior. bioRxiv. 2014:002873. https://doi.org/10.1101/002873.
Honegger K, de Bivort B. Stochasticity, individuality and behavior. Curr Biol. 2018; 28(1):8–12.
Google Scholar
Hughey LF, Hein AM, Strandburg-Peshkin A, Jensen FH. Challenges and solutions for studying collective animal behaviour in the wild. Philos Trans R Soc B Biol Sci. 2018; 373(1746):20170005.
Google Scholar
Raoult V, Tosetto L, Williamson J. Drone-based high-resolution tracking of aquatic vertebrates. Drones. 2018; 2(4):37.
Google Scholar
Willis M, Koenig C, Black S, Castaneda A. Archeological 3d mapping: the structure from motion revolution. J Tex Archeology Hist. 2016; 3:1–36.
Google Scholar
Barber A, Cosker D, James O, Waine T, Patel R. Camera tracking in visual effects an industry perspective of structure from motion: 2016. p. 45–54. https://doi.org/10.1145/2947688.2947697.
He K, Gkioxari G, Dollár P, Girshick R. Mask r-cnn. In: Computer Vision (ICCV), 2017 IEEE International Conference On. IEEE: 2017. p. 2980–8.
Abdulla W. Mask R-CNN for object detection and instance segmentation on Keras and TensorFlow. GitHub repository. 2017. https://github.com/matterport/Mask_RCNN.
Lin T, Maire M, Belongie SJ, Bourdev LD, Girshick RB, Hays J, Perona P, Ramanan D, Dollár P, Zitnick CL. Microsoft COCO: common objects in context. CoRR. 2014; abs/1405.0312. http://arxiv.org/abs/1405.0312.
Torrey L, Shavlik J. Transfer learning. In: Handbook of Research on Machine Learning Applications and Trends: Algorithms, Methods, and Techniques. IGI Global: 2010. p. 242–264.
Kuhn HW. The hungarian method for the assignment problem. Nav Res Logist Q. 1955; 2(1-2):83–97.
Google Scholar
Hartley R, Zisserman A. Multiple View Geometry in Computer Vision, 2nd edn. New York: Cambridge University Press; 2003.
Google Scholar
Westoby MJ, Brasington J, Glasser NF, Hambrey MJ, Reynolds J. ’structure-from-motion’photogrammetry: A low-cost, effective tool for geoscience applications. Geomorphology. 2012; 179:300–14.
Google Scholar
Fonstad MA, Dietrich JT, Courville BC, Jensen JL, Carbonneau PE. Topographic structure from motion: a new development in photogrammetric measurement. Earth Surf Process Landf. 2013; 38(4):421–30.
Google Scholar
Linda G, Shapiro CG. Stockman, Computer vision. Upper Saddle River: Prentice Hall; 2001.
Google Scholar
Bradski G. The OpenCV Library: Dr. Dobb’s Journal of Software Tools; 2000.
Schönberger JL, Frahm J-M. Structure-from-motion revisited. In: IEEE Conference on Computer Vision and Pattern Recognition (CVPR): 2016. https://doi.org/10.1109/cvpr.2016.445.
Schönberger JL, Zheng E, Pollefeys M, Frahm J-M. Pixelwise view selection for unstructured multi-view stereo. In: European Conference on Computer Vision (ECCV): 2016. https://doi.org/10.1007/978-3-319-46487-9_31.
Shoemake K. Animating rotation with quaternion curves. In: Proceedings of the 12th Annual Conference on Computer Graphics and Interactive Techniques: 1985. p. 245–54. https://doi.org/10.1145/325334.325242.
Nührenberg P. multiviewtracks: animal trajectories from multiple-view videos. Zenodo. 2020. https://doi.org/10.5281/zenodo.3666727.
Lennox RJ, Aarestrup K, Cooke SJ, Cowley PD, Deng ZD, Fisk AT, Harcourt RG, Heupel M, Hinch SG, Holland KN, et al. Envisioning the future of aquatic animal tracking: technology, science, and application. BioScience. 2017; 67(10):884–96.
Google Scholar
Kalacska M, Lucanus O, Sousa L, Vieira T, Arroyo-Mora J. Freshwater fish habitat complexity mapping using above and underwater structure-from-motion photogrammetry. Remote Sens. 2018; 10(12):1912.
Google Scholar
Figueira W, Ferrari R, Weatherby E, Porter A, Hawes S, Byrne M. Accuracy and precision of habitat structural complexity metrics derived from underwater photogrammetry. Remote Sens. 2015; 7(12):16883–900.
Google Scholar
Ward A, Webster M. Sociality: the behaviour of group-living animals. 2016. https://doi.org/10.1007/978-3-319-28585-6_1.
Ebersole JP. Niche separation of two damselfish species by aggression and differential microhabitat utilization. Ecology. 1985; 66(1):14–20. https://doi.org/10.2307/1941302. http://arxiv.org/abs/https://esajournals.onlinelibrary.wiley.com/doi/pdf/10.2307/1941302.
Google Scholar
Sturmbauer C, Fuchs C, Harb G, Damm E, Duftner N, Maderbacher M, Koch M, Koblmüller S. Abundance, distribution, and territory areas of rock-dwelling lake tanganyika cichlid fish species In: Wilke T, Väinölä R, Riedel F, editors. Patterns and Processes of Speciation in Ancient Lakes. Dordrecht: Springer: 2009. p. 57–68.
Google Scholar
Akkaynak D, Treibitz T. Sea-thru: A method for removing water from underwater images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition: 2019. p. 1682–91. https://doi.org/10.1109/cvpr.2019.00178.
Knapitsch A, Park J, Zhou Q-Y, Koltun V. Tanks and temples: Benchmarking large-scale scene reconstruction. ACM Trans Graph. 2017; 36(4).
Bianco S, Ciocca G, Marelli D. Evaluating the performance of structure from motion pipelines. J Imaging. 2018; 4(8):98.
Google Scholar
Romero-Ferrero F, Bergomi MG, Hinz RC, Heras FJ, de Polavieja GG. Idtracker.ai: tracking all individuals in small or large collectives of unmarked animals. Nat Methods. 2019; 16(2):179–82.
CAS
PubMed
Google Scholar
Todd JG, Kain JS, de Bivort BL. Systematic exploration of unsupervised methods for mapping behavior. Phys Biol. 2017; 14(1):015002.
PubMed
Google Scholar
Wiltschko AB, Johnson MJ, Iurilli G, Peterson RE, Katon JM, Pashkovski SL, Abraira VE, Adams RP, Datta SR. Mapping sub-second structure in mouse behavior. Neuron. 2015; 88(6):1121–35.
CAS
PubMed
PubMed Central
Google Scholar
Zuffi S, Kanazawa A, Black MJ. Lions and tigers and bears: Capturing non-rigid, 3d, articulated shape from images. In: Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition: 2018. p. 3955–63. https://doi.org/10.1109/cvpr.2018.00416.
Robie AA, Seagraves KM, Egnor SR, Branson K. Machine vision methods for analyzing social interactions. J Exp Biol. 2017; 220(1):25–34.
PubMed
Google Scholar
Pereira TD, Aldarondo DE, Willmore L, Kislin M, Wang SS-H, Murthy M, Shaevitz JW. Fast animal pose estimation using deep neural networks. bioRxiv. 2018:331181. https://doi.org/10.1101/331181.
Brown AE, de Bivort B. Ethology as a physical science. Nat Phys. 2018; 1. https://doi.org/10.1038/s41567-018-0093-0.
Jordan LA, Ryan MJ. The sensory ecology of adaptive landscapes. Biol Lett. 2015; 11(5):20141054.
PubMed
PubMed Central
Google Scholar
Anderson DJ, Perona P. Toward a science of computational ethology. Neuron. 2014; 84(1):18–31.
CAS
PubMed
Google Scholar