Digitala Vetenskapliga Arkivet

Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
2D Modelling of Phytoplankton Dynamics in Freshwater Lakes
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Information Technology, Division of Scientific Computing.
2019 (Swedish)Independent thesis Advanced level (professional degree), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

Phytoplankton are single celled organisms capable of phytosynthesis, and are present in all the major oceans and lakes in the world. Phytoplankton contribute to 50% of the total primary production on Earth, and are the dominating primary producer in most aquatic ecosystems. This thesis is based on the 1D deterministic model by Jäger et. al. (2010) which models phytoplankton dynamics in freshwater lakes, where phytoplankton growth is limited by the availability of light and phosphorus. The original model is here extended to two dimensions to include a horizontal dimension as well as a vertical dimension, in order to simulate phytoplankton dynamics under varying lake bottom topographies. The model was solved numerically using a grid transform and a finite volume method in MATLAB. Using the same parameter settings as the 1D case studied by Jäger et. al. (2010), an initial study of plankton dynamics was done by varying the horizontal and vertical diffusion coefficients independently.

Place, publisher, year, edition, pages
2019. , p. 34
Series
UPTEC F, ISSN 1401-5757 ; 19015
Keywords [en]
Modelling, computational ecology, ecology, ecosystems, lake ecosystems, deterministic modelling, finite volume method, phytoplankton, plankton, lake, lakes
National Category
Bioinformatics (Computational Biology) Ecology
Identifiers
URN: urn:nbn:se:uu:diva-388868OAI: oai:DiVA.org:uu-388868DiVA, id: diva2:1335697
External cooperation
ICELAB Umeå Universitet
Educational program
Master Programme in Engineering Physics
Supervisors
Examiners
Available from: 2019-08-06 Created: 2019-07-06 Last updated: 2019-08-06Bibliographically approved

Open Access in DiVA

fulltext(5413 kB)573 downloads
File information
File name FULLTEXT01.pdfFile size 5413 kBChecksum SHA-512
7931bba70935e0721fea7a8bc20ec6e2166724570bc476a5ee2ff03ac6b2589f0f4e4d2192d650be7e5c50a0f3f1243fc051b7a6a5309aac32024ab78a8fa004
Type fulltextMimetype application/pdf

By organisation
Division of Scientific Computing
Bioinformatics (Computational Biology)Ecology

Search outside of DiVA

GoogleGoogle Scholar
Total: 577 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 427 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf