Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/11752
Title: MAXIMIZING PHYLOGENETIC DIVERSITY IN THE SELECTION OF CONTIGUOUS CONSERVATION AREAS
Authors: Atluri, Gowtham
Keywords: ELECTRONICS AND COMPUTER ENGINEERING;PHYLOGENETIC DIVERSITY;CONSERVATION;GENETIC ALGORITHM
Issue Date: 2007
Abstract: In the biological conservation literature, the optimum reserve site selection prob-lem has often been addressed by using the prototype set covering and maximal covering formulations, assuming that representation of species is the only cri-terion in site selection. This approach usually results in a small but highly fragmented reserve, which is not useful for practical conservation planning. The spatial layout of the reserve is a particularly important concern when designing an efficient reserve network, given the potential role of inter-site dis-persal in species' regional persistence. Spatial attributes such as compactness, adjacency, connectivity, and proximity of the selected sites can be as important as minimizing the number of selected sites. To improve the chances of species persistence, it may be desirable to reduce habitat fragmentation and select a contiguous set of reserve sites. Phylogenetic diversity score is a measure of biodiversity, which needs to be maximized when choosing reserve sites for conservation. The problem of select-ing a contiguous set of reserve sites at the same time maximizing phylogenetic diversity can be represented as a linear integer programming problem. Using the formal optimization is inappropriate given a large set of taxa and a large number of reserve sites. This certainly calls for an efficient algorithm in selecting conservation areas. v Abstract In this work, "Maximizing Phylogenetic Diversity in the Conservation of Con-tiguous Conservation Areas", a Genetic Algorithm is proposed to obtain a con-tiguous reserve network for conservation. Also, the possibility of a greedy algo-rithm is explored. The proposed Genetic Algorithm based approach has been compared with the existing formal optimization techniques and the superiority of the proposed method is made explicit. vi
URI: http://hdl.handle.net/123456789/11752
Other Identifiers: M.Tech
Research Supervisor/ Guide: Joshi, R. C.
metadata.dc.type: M.Tech Dessertation
Appears in Collections:MASTERS' DISSERTATIONS (E & C)

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