Past Postdoctoral Fellow

Kotaro was a postdoctoral fellow with a joint appointment at the Alaska Fisheries Science Center and the University of Washington. His primary research interests relate to sustainable fisheries management and encompass data analysis, statistical modelling, stock assessment, and management strategy evaluation. Kotaro got his PhD in Fisheries Science from the School of Aquatic and Fishery Science (SAFS) at the University of Washington under the advisement of Dr. Ray Hilborn. Prior to that, he got his Masters in Zoology from SAFS, and from L’école nationale supérieure agronomique de Rennes, in France.

Publications

1. Ono, K, Haynie, AC, Hollowed, AB, Ianelli, JN, McGilliard, CR, Punt, AE. 2017. Management strategy analysis for multispecies fisheries including technical interactions and human behavior in modeling management decisions and fishing. Can. J. Fish. Aquat. Sci. 00:00-00, doi:10.1139/cjfas-2017-0135.
2. Ono, K, Ianelli, JN, McGilliard, CR, Punt, AE. 2017. Integrating data from multiple surveys and accounting for spatio-temporal correlation to index the abundance of juvenile Pacific halibut in Alaska. ICES J. Mar. Sci. 00:00-00. doi:10.1093/icesjms/fsx174.
3. Kuriyama, PT, Ono, K, Hurtado-Ferro, F, Hicks, AC, Taylor, IG, Licandeo, RR, Johnson, KF, Anderson, SC, Monnahan, CC, Rudd, MB, Stawitz, CC, Valero, JL. 2016. An empirical weight-at-age approach reduces estimation bias compared to modeling parametric growth in integrated, statistical stock assessment models when growth is time varying. Fish Res. 180: 119-127. doi:10.1016/j.fishres.2015.09.007.
4. Monnahan, CC, Ono, K, Anderson, SC, Rudd, MB, Hicks, AC, Hurtado-Ferro, F, Johnson, KF, Kuriyama, PT, Licandeo, RR, Stawitz, CC, Taylor, IG, Valero, JL. 2016. The effect of length bin width on growth estimation in integrated age-structured stock assessments. Fish. Res. 180: 103-112. doi:10.1016/j.fishres.2015.11.002
5. Brieuc, MSO, Ono, K, Drinan, DP, Naish, KA. 2015. Integration of Random Forest with population‐based outlier analyses provides insight on the genomic basis and evolution of run timing in Chinook salmon (Oncorhynchus tshawytscha). Molecular Ecol. 24: 2729-2746. doi: 10.1111/mec.13211
6. Ward, EJ, Jannot, JE, Lee, YW, Ono, K, Shelton, AO, Thorson, JT. 2015. Using spatiotemporal species distribution models to identify temporally evolving hotspots of species co-occurrence. Eco. App. doi: 10.1890/15-0051.1
7. Ono, K, Shelton, AO, Ward, EJ, Thorson, JT, Feist, BE, Hilborn, R. 2015. Space-time investigation of the effects of fishing on fish populations. Eco. App. doi: 10.1890/14-1874.1
8. Thorson, JT, Ianelli, JN, Munch, SB, Ono, K, Spencer, PD. 2015. Spatial delay-difference models for estimating spatiotemporal variation in juvenile production and population abundance. Can. J. Fish. Aquat. Sci. doi: 10.1139/cjfas-2014-0543
9. Ono, K, Punt, AE, and Hilborn, R. 2015. Think outside the grids: An objective approach to define spatial strata for catch and effort analysis. Fisheries Res. 170: 89-101. doi: 10.1016/j.fishres.2015.05.021
10. Ono, K, Punt, AE, and Hilborn, R. 2015. How do marine closures affect the analysis of catch and effort data? Can. J. Fish. Aquat. Sci. 72:1-14. doi: 10.1139/cjfas-2014-0146