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" Structure, Aboveground Biomass, and Soil Characterization of Avicennia marina in Eastern Mangrove Lagoon National Park, Abu Dhabi "
Tareefa Saad Sultan Alsumaiti
Tullis, Jason
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Latin Dissertation
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| Language of Document
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English
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| Record Number
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803256
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| Doc. No
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TL48038
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| Call number
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1640738182; 3646874
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| Main Entry
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Elsayed, Ahmed
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| Title & Author
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Structure, Aboveground Biomass, and Soil Characterization of Avicennia marina in Eastern Mangrove Lagoon National Park, Abu Dhabi\ Tareefa Saad Sultan AlsumaitiTullis, Jason
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| College
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University of Arkansas
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| Date
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2014
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| Degree
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Ph.D.
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| field of study
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Environmental Dynamics
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| student score
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2014
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| Page No
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106
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| Note
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Committee members: Limp, Fredrick; Paradise, Thomas
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| Note
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Place of publication: United States, Ann Arbor; ISBN=978-1-321-36937-3
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| Abstract
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Mangrove forests are national treasures of the United Arab Emirates (UAE) and other arid countries with limited forested areas. Mangroves form a crucial part of the coastal ecosystem and provide numerous benefits to society, economy, and especially the environment. Mangrove trees, specifically <i>Avicennia marina,</i> are studied in their native habitat in order to characterize their population structure, aboveground biomass, and soil properties. This study focused on Eastern Mangrove Lagoon National Park in Abu Dhabi, which was the first mangrove protected area to be designated in UAE. <i>In situ</i> measurements were collected to estimate Avicennia marina status, mortality rate (%), height (m), crown spread (m), stem number, diameter at breast height (cm), basal area (m), and aboveground biomass (t ha<sup>-1 </sup>). Small-footprint aerial light detection and ranging (LIDAR) data acquired by UAE were processed to characterize mangrove canopy height and aboveground biomass density. This included extraction of LIDAR-derived height percentile statistics, segmentation of the forest into structurally homogenous units, and development of regression relationships between <i>in situ </i> reference and remote sensing data using a machine learning approach. An <i>in situ</i> soil survey was conducted to examine the soils' physical and chemical properties, fertility status, and organic matter. The data of soil survey were used to create soil maps to evaluate key characteristics of soils, and their influence on <i>Avicennia marina </i> in Eastern Mangrove Lagoon National Park. The results of this study provide new insights into <i>Avicennia marina</i> canopy population, structure, aboveground biomass, and soil properties in Abu Dhabi, as data in such arid environments is lacking. This valuable information can help in managing and preserving this unique ecosystem.
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| Subject
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Geographic information science; Soil sciences; Remote sensing
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| Descriptor
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Biological sciences;Earth sciences;Aboveground biomass;Avicennia marina;Lidar;Population;Soil characterization;Structural properties
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| Added Entry
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Tullis, Jason
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Environmental DynamicsUniversity of Arkansas
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