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   <subfield code="a">Rollan, Therese Anne M.</subfield>
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   <subfield code="a">Development of a framework for a functional-structural seagrass transplantation simulation using GAMA platform</subfield>
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   <subfield code="a">xvi, 82 leaves</subfield>
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   <subfield code="a">Thesis (Master of Science in Geomatics Engineering)--University of the Philippines Diliman</subfield>
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   <subfield code="a">Seagrasses are clonal flowering plants that share the same architecture, submerged in shallow marine waters, usually located on semi-enclosed lagoons, along coastlines, and co-existing with intertidal mangroves and corals. They play an important role in providing food and shelter for various marine species, stabilizing the sea bottom, maintaining water quality, supporting the livelihood of local economies and contributes greatly on holding the ocean carbon stock.     With the Philippines being entirely delineated with shorelines and surrounded by seas, large portions of relatively shallow depths are occupied by seagrass beds. However, a massive decrease in its coverage has been observed in the past several years. Long term threat to seagrass habitat results from coastal eutrophication as a result of overfeeding in fish cages, effluent from industrial, commercial and domestic facilities, inadequate septic systems, human wastes, and storm drain runoff carrying organic waste and fertilizers. Moreover, extreme events such as typhoons cause damage and even wipe out wide areas of seagrasses. With the increasing onset of strong weather disturbances, it is key to observe the changes and probable damage in seagrass habitat and develop a way to scientifically back up recovery strategies such as transplantation to increase the probability of rehabilitation success.     In line with these concerns, this study describes the development of a framework for a transplantation scenario evaluation tool that performs geosimulation for Thalassia hemprichii at specified plots within an uproot site located in New Quezon, Busuanga, Palawan, Philippines. The tool is implemented in GAMA (GIS Agent-based Modeling Architecture) Platform and accessible VIa this link: https://drive.google.comiopen?id=1rxh2PLRpOQIYdG6031uOmGvR2noT5FZJ. The platform provides a user/developer interface that features user input panel, multi-layer displays, statistical reporting and agent inspection which in the future would be able to assist local communities, government authorities, environmentalists, ecologists and other researchers to formulate effective strategies not only for seagrass recovery but also for its protection, rehabilitation and conservation.     In this study, majority of the responses show that factor A: Planting Distribution has a greater weight than factor B: Planting Density. Two responses, Mean and Standard Deviation, were used to determine which scenario will fit given the initial percent cover of a plot -- Scenario 1 having 4 plants with 24 cm intervals for Plot 1 and Plot 2, while Scenario 2 having 8 plants (2 plants per grid cell) with 24 em intervals for Plot 3.</subfield>
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   <subfield code="a">Macatulad, Edgardo G.</subfield>
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