Thesis (Ph. D.)--University of Hong Kong, 1994. / Includes bibliographical references (leaves 275-295).

Thesis (M.S.)--Oregon State University, 1993. / Typescript (photocopy). Includes bibliographical references (leaves 85-87). Also available on the World Wide Web.

Thesis (Ph. D.)--University of Washington, 1996. / Vita. Includes bibliographical references.

Thesis (Ph. D.)--University of Rhode Island, 2005. / Typescript. Includes bibliographical references (leaves 253-257).

Thesis (M.S.)--Oregon State University, 2006. / Printout. Includes bibliographical references (leaves 142-152). Also available on the World Wide Web.

Production dynamics in the phytoplankton community of a mesotrophic Texas reservoir were measured weekly over a four month period using 14C incubation and ATP assay methodologies. Assimilation values of 14C ranged from 0.2 to 45 ug C 1 hr1 - . Significant positive and occasionally negative changes in biomass (i.e. viable organic carbon) were observed in short term (4 hr) in situ incubations juxtapo-sitioned with the 14C experiments; viable organic carbon production, estimated with the ATP assay, ranged from -25 to +50 ug C 1l1hr1. Carbon assimilation and biomass changes did not correlate in either short term (4-5 hr.) or over the study period (6 months). However, weekly biomass trends were predicted by relative positive or negative biomass changes in the short term incubations. Biomass measurements gave a more sensitive insight into production dynamics in the phytoplankton community than did carbon assimilation measurements.

Thesis (S.M.)--Joint Program in Biological Oceanography (Massachusetts Institute of Technology, Dept. of Biology; and the Woods Hole Oceanographic Institution), 2008. / "February 2008." / Includes bibliographical references (p. 133). / I build on the deterministic phytoplankton growth model of Sosik et al. by introducing process error, which simulates real variation in population growth and inaccuracies in the structure of the matrix model. Adding a stochastic component allows me to use maximum likelihood methods of parameter estimation. I lay out the method used to calculate parameter estimates, confidence intervals, and estimated population growth rates, then use a simplified three-stage model to test the efficacy of this method with simulated observations. I repeat similar tests with the full model based on Sosik et al., then test this model with a set of data from a laboratory culture whose population growth rate was independently determined. In general, the parameter estimates I obtain for simulated data are better the lower the levels of stochasticity. Despite large confidence intervals around some model parameter estimates, the estimated population growth rates have relatively small confidence intervals. The parameter estimates I obtained for the laboratory data fell in a region of the parameter space that in general contains parameter sets that are difficult to estimate, although the estimated population growth rate was close to the independently determined value. / by Lorraine Thomas. / S.M.

Thesis (Ph.D.)--McMaster University, 2006. / Supervisor: Patricia Chow-Fraser. Includes bibliographical references.

Graduation date: 1992

Thesis (Ph. D.)--University of Washington, 2003. / Vita. Includes bibliographical references (leaves 125-140).