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Department of Oceanography

A novel quantitative, sub-provincial approach to characterizing the shape of chlorophyll profiles

Abstract

dc:description.abstract

In this study, novel approaches such as artificial neural networks and generalized modelling have highlighted the variability in profile shape and enabled its improved prediction. This will lead to superior regional estimates of primary production.

Degree

thesis:*
Grantor dc:publisher.institution
Department of Oceanography
Year dc:date.issued
2001

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Silulwane, Nonkqubela F
Advisors dc:contributor.advisor
  • Richardson, Anthony J
  • Mitchell-Innes, Betty A
  • Shillington, Frank

Rights

Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/11427/12582
OAI identifier oai:identifier
oai:open.uct.ac.za:11427/12582

Chain of custody

source
Harvested from
University of Cape Town
Base URL
open.uct.ac.za/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
related terms
citation

Silulwane, Nonkqubela F. A novel quantitative, sub-provincial approach to characterizing the shape of chlorophyll profiles. Department of Oceanography, 2001. http://hdl.handle.net/11427/12582