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Papers using TMB

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Jim Thorson edited this page Jun 21, 2016 · 35 revisions

List of papers that uses TMB (first come, first served):

In press

  • C. Konrad, N.G. Cadigan, and J. Brattey. 2016. Reporting rate of tagging experiments for cod (Gadus morhua). Environmental and Ecological Statistics. In press. http://link.springer.com/article/10.1007/s10651-016-0344-0?wt_mc=internal.event.1.SEM.ArticleAuthorOnlineFirst
  • Thorson, J.T., Fonner, R., Haltuch, M., Ono, K., and Winker, H. In press. Accounting for spatiotemporal variation and fisher targeting when estimating abundance from multispecies fishery data. Can. J. Fish. Aquat. Sci. doi:10.1139/cjfas-2015-0598.
  • Thorson, J.T., Ianelli, J.N., Larsen, E., Ries, L., Scheuerell, M.D., Szuwalski, C., and Zipkin, E. In press. Joint dynamic species distribution models: a tool for community ordination and spatiotemporal monitoring. Glob. Ecol. Biogeogr.
  • Thorson, J.T., Jannot, J.E., and Somers, K. In press. Using spatio-temporal models of population growth and movement to monitor overlap between human impacts and population density. J. Appl. Ecol.
  • Thorson, J.T., Pinsky, M.L., and Ward, E.J. In press. Model-based inference for estimating shifts in species distribution, area occupied and centre of gravity. Methods Ecol. Evol. doi:10.1111/2041-210X.12567.

2016

  • Kristensen, K., Nielsen, A., Berg, C.W., Skaug, H.J., Bell, B. 2016, TMB: Automatic Differentiation and Laplace Approximation https://www.jstatsoft.org/article/view/v070i05
  • Cadigan, N.G. 2016. A state-space stock assessment model for northern cod, including under-reported catches and variable natural mortality rates." Canadian Journal of Fisheries and Aquatic Sciences 73(2), 296-308
  • Webber, D.N., and Thorson, J.T. 2016. Variation in growth among individuals and over time: A case study and simulation experiment involving tagged Antarctic toothfish. Fish. Res. 180: 67–76. doi:10.1016/j.fishres.2015.08.016.

2015

  • Thorson, J.T., Ianelli, J.N., Munch, S.B., Ono, K., and Spencer, P.D. 2015. Spatial delay-difference models for estimating spatiotemporal variation in juvenile production and population abundance. Can. J. Fish. Aquat. Sci. 72(12): 1897–1915. doi:10.1139/cjfas-2014-0543.
  • James T. Thorson, Hans Skaug, Kasper Kristensen, Andrew O. Shelton, Eric J. Ward, John Harms, Jim Benante. 2015. The importance of spatial models for estimating the strength of density dependence. Ecology. 96:1202–1212. http://www.esajournals.org/doi/abs/10.1890/14-0739.1
  • James T. Thorson, Andrew O. Shelton, Eric J. Ward, and Hans Skaug. 2015. Geostatistical delta-generalized linear mixed models improve precision for estimated abundance indices for West Coast groundfishes. ICES Journal of Marine Science. 72 (5): 1297-1310. http://icesjms.oxfordjournals.org/content/72/5/1297.abstract?etoc
  • Thorson, J.T., Scheuerell, M.D., Shelton, A.O., See, K.E., Skaug, H.J., and Kristensen, K. 2015. Spatial factor analysis: a new tool for estimating joint species distributions and correlations in species range. Methods Ecol. Evol. 6(6): 627–637. doi:10.1111/2041-210X.12359.
  • Thorson, J. 2015. Spatio-temporal variation in fish condition is not consistently explained by density, temperature, or season for Northeast Pacific groundfishes. Mar. Ecol. Progress Series. 526:101-112. http://www.int-res.com/abstracts/meps/v526/p101-112/
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