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Estimating phytoplankton growth rates from compositional data

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dc.contributor.advisor Michael Neubert and Heidi Sosik. en_US
dc.contributor.author Thomas, Lorraine (Lorraine Marie) en_US
dc.contributor.other Woods Hole Oceanographic Institution. en_US
dc.date.accessioned 2008-12-11T18:22:05Z
dc.date.available 2008-12-11T18:22:05Z
dc.date.issued 2008 en_US
dc.identifier.uri http://hdl.handle.net/1721.1/43755
dc.description Thesis (S.M.)--Joint Program in Biological Oceanography (Massachusetts Institute of Technology, Dept. of Biology; and the Woods Hole Oceanographic Institution), 2008. en_US
dc.description "February 2008." en_US
dc.description Includes bibliographical references (p. 133). en_US
dc.description.abstract 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. en_US
dc.description.statementofresponsibility by Lorraine Thomas. en_US
dc.format.extent 133 p. en_US
dc.language.iso eng en_US
dc.publisher Massachusetts Institute of Technology en_US
dc.rights M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. en_US
dc.rights.uri http://dspace.mit.edu/handle/1721.1/7582 en_US
dc.subject Joint Program in Biological Oceanography. en_US
dc.subject Biology. en_US
dc.subject Woods Hole Oceanographic Institution. en_US
dc.subject.lcsh Phytoplankton en_US
dc.subject.lcsh Primary productivity (Biology) Computer simulation en_US
dc.title Estimating phytoplankton growth rates from compositional data en_US
dc.type Thesis en_US
dc.description.degree S.M. en_US
dc.contributor.department Joint Program in Biological Oceanography. en_US
dc.contributor.department Massachusetts Institute of Technology. Dept. of Biology. en_US
dc.contributor.department Woods Hole Oceanographic Institution. en_US
dc.identifier.oclc 232607185 en_US


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