Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa

 

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dc.contributor.advisor Field, John G en_ZA
dc.contributor.advisor Wickens, Patti en_ZA
dc.contributor.author Savage, Candida en_ZA
dc.date.accessioned 2014-11-05T17:41:22Z
dc.date.available 2014-11-05T17:41:22Z
dc.date.issued 1996 en_ZA
dc.identifier.citation Savage, C. 1996. Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa. University of Cape Town. en_ZA
dc.identifier.uri http://hdl.handle.net/11427/9272
dc.description Bibliography: leaves 90-95. en_ZA
dc.description.abstract The strategy for analysing multivariate data presented by Field et. al. (1982) was tested for its sensitivity in detecting the effects of offshore marine mining on macrobenthic communities. The technique has proven to be particularly sensitive and robust in elucidating changes in the structure of marine communities following organic pollution events. The primary aim of this study was to investigate its applicability in discerning community changes in an area exposed to physical disturbance of the seabed. Statistical testing, using analysis of similarities, reveals a highly significant difference between mined and unmined samples. Statistical testing also detects natural spatial heterogeneity across the 6 study areas. Aggregation of the data to higher taxonomic levels did not result in the loss of information, and in fact, improved the resolution of the community patterns. Multivariate analyses were therefore performed using the community data aggregated to genus-level. Hierarchical agglomerative clustering reveals two major groups of samples, the mined and the unmined samples. en_ZA
dc.language.iso eng en_ZA
dc.subject.other Zoology en_ZA
dc.title Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa en_ZA
dc.type Master Thesis
uct.type.publication Research en_ZA
uct.type.resource Thesis en_ZA
dc.publisher.institution University of Cape Town
dc.publisher.faculty Faculty of Science en_ZA
dc.publisher.department Department of Biological Sciences en_ZA
dc.type.qualificationlevel Masters
dc.type.qualificationname MSc en_ZA
uct.type.filetype Text
uct.type.filetype Image
dc.identifier.apacitation Savage, C. (1996). <i>Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa</i>. (Thesis). University of Cape Town ,Faculty of Science ,Department of Biological Sciences. Retrieved from http://hdl.handle.net/11427/9272 en_ZA
dc.identifier.chicagocitation Savage, Candida. <i>"Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa."</i> Thesis., University of Cape Town ,Faculty of Science ,Department of Biological Sciences, 1996. http://hdl.handle.net/11427/9272 en_ZA
dc.identifier.vancouvercitation Savage C. Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa. [Thesis]. University of Cape Town ,Faculty of Science ,Department of Biological Sciences, 1996 [cited yyyy month dd]. Available from: http://hdl.handle.net/11427/9272 en_ZA
dc.identifier.ris TY - Thesis / Dissertation AU - Savage, Candida AB - The strategy for analysing multivariate data presented by Field et. al. (1982) was tested for its sensitivity in detecting the effects of offshore marine mining on macrobenthic communities. The technique has proven to be particularly sensitive and robust in elucidating changes in the structure of marine communities following organic pollution events. The primary aim of this study was to investigate its applicability in discerning community changes in an area exposed to physical disturbance of the seabed. Statistical testing, using analysis of similarities, reveals a highly significant difference between mined and unmined samples. Statistical testing also detects natural spatial heterogeneity across the 6 study areas. Aggregation of the data to higher taxonomic levels did not result in the loss of information, and in fact, improved the resolution of the community patterns. Multivariate analyses were therefore performed using the community data aggregated to genus-level. Hierarchical agglomerative clustering reveals two major groups of samples, the mined and the unmined samples. DA - 1996 DB - OpenUCT DP - University of Cape Town LK - https://open.uct.ac.za PB - University of Cape Town PY - 1996 T1 - Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa TI - Multivariate analyses of the impact of offshore marine mining on the benthic macrofauna off the west coast of Southern Africa UR - http://hdl.handle.net/11427/9272 ER - en_ZA


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