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PHIL PATTON

PhD student

Phil is a NOAA QUEST Fellow with the Cetacean Research Program at the Pacific Islands Fisheries Science Center. For his dissertation, he’s researching ways to improve stock assessments of non-migratory dolphins in Hawaiʻi. This includes automating photo-identification of these animals, understanding how these automated tools interact with capture-recapture models, and estimating demographic parameters using cutting edge methods in capture recapture.

email: pattonp@hawaii.edu

philpatton.github.io

For publication pdfs, please visit the following links:

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biography

 

Biography

Phil earned a B.S. in Conservation Biology from the State University of New York College of Environmental Science and Forestry in 2013, followed by a M.S. in Fisheries, Wildlife, and Conservation Biology from North Carolina State University in 2016. His thesis research explored methods for incorporating species interactions and false positive sampling errors in site-occupancy models. After completing his master's degree, Phil worked as a data analyst in the public and private sectors. In this time, he developed his analytical and coding skills, particularly while working on a software development team in industry. His dissertation research is funded by the NOAA Quantitative Ecology and Socioeconomics Training (QUEST) program, which trains the next generation of management-focused researchers.

 

Publications

 

2023

Patton, P.T., Cheeseman, T., Abe, K., Yamaguchi, T., Reade, W., Southerland, K., Howard, A., Oleson, E.M., Allen, J.B., Ashe, E., Athayde, A., Baird, R.W., Basran, C., Cabrera, E., Calambokidis, J., Cardoso, J., Carroll, E.L., Cesario, A., Cheney, B.J., Corsi, E., Currie, J., Durban, J.W., Falcone, E.A., Fearnbach, H., Flynn, K., Franklin, T., Franklin, W., Vernazzani, B.G., Genov, T., Hill, M., Johnston, D.R., Keene, E.L., Mahaffy, S.D., McGuire, T.L., McPherson, L., Meyer, C., Michaud, R., Miliou, A., Orbach, D.N., Pearson, H.C., Rasmussen, M.H., Rayment, W.J., Rinaldi, C., Rinaldi, R., Siciliano, S., Stack, S., Tintore, B., Torres, L.G., Towers, J.R., Trotter, C., Moore, R.T., Weir, C.R., Wellard, R., Wells, R., Yano, K.M., Zaeschmar, J.R. & Bejder, L. (2023) A deep learning approach to photo–identification demonstrates high performance on two dozen cetacean species. Methods in Ecology and Evolution, 00, 1--1, https://besjournals.pericles-prod.literatumonline.com/doi/10.1111/2041-210X.14167.

 

 

2022

Patton, P., Pacifici, K., Collazo, J.,  May 2022.  Modeling and estimating co‑occurrence between the invasive Shiny Cowbird and its Puerto Rican hosts. Biological Invasions. 

publications
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