Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.557664
Title: Quantifying biodiversity for valuation
Author: Lyashevska, O.
Awarding Body: Queen's University Belfast
Current Institution: Queen's University Belfast
Date of Award: 2012
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Abstract:
Biodiversity, arising at multiple levels, is known as a multi-dimensional and complex concept, but is also known to have a rather loose definition. Imprecise definitions are not very suitable for objective quantification or the rigour of economic valuation. Therefore, to construct a more substantial definition of value for biodiversity, a theoretical argument aiming to link biodiversity and functional (meaningful) information needs to be developed. A working hypothesis is that biodiversity is a measure of the total difference within a biological system, which can be summarised in terms of the system's total information content, of which functional information is a subset. Since functional information has systematic (non-random) Patterns, it therefore, coincides with the scientific meaning of biological complexity, thus providing the foundation of value in biodiversity. The theory presented sets the goal of estimating biological complexity from the potentially valuable information derived from empirical biodiversity metric data (ecological measures). To achieve this, the ecological properties ofa system, as they are measured by ecologists, were translated into a simply defined single valued property. This led to a conclusion that ifthere exists a systematic relationship among empirical biodiversity metrics, then there must be a unifying property underlying intrinsic value ofbiodiversity. Then, an advantage of a representation of biodiversity as information was demonstrated by comparing it with the most commonly used metric - species richness. It was shown that species richness missed a large proportion of diversity, emphasising the importance of additional ecological properties and the need for species databases to record functional traits, presence and abundances in communities, as well as phylogenetic information. Finally, by providing intellectual foundations and developing an analytical tool for biodiversity quantification, this study sets the goal for further research.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.557664  DOI: Not available
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