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An integrated modeling approach for ...

Walker, Samuel Peter.

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An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary.

Record Type:	Language materials, printed : Monograph/item
Title/Author:	An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary./
Author:	Walker, Samuel Peter.
Description:	144 p.
Notes:	Adviser: Dwayne E. Porter.
Contained By:	Dissertation Abstracts International68-08B.
Subject:	Biology, Ecology. -
Online resource:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3280367
ISBN:	9780549212249

An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary.
Walker, Samuel Peter.

An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary. - 144 p.

Adviser: Dwayne E. Porter.

Thesis (Ph.D.)--University of South Carolina, 2007.

Keywords. Invasive species, estuary, NERRS, Phragmites, GIS-based models, remote sensing, coastal resource management, geographic information processing.

ISBN: 9780549212249Subjects--Topical Terms:

1017726
Biology, Ecology.

An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary.
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020 $a 9780549212249
035 $a (UMI)AAI3280367
035 $a AAI3280367
040 $a UMI $c UMI
100 1 $a Walker, Samuel Peter. $3 1264117
245 1 3 $a An integrated modeling approach for monitoring and predicting common reed (Phragmites australis) colonization in a managed South Carolina estuary.
300 $a 144 p.
500 $a Adviser: Dwayne E. Porter.
500 $a Source: Dissertation Abstracts International, Volume: 68-08, Section: B, page: 4962.
502 $a Thesis (Ph.D.)--University of South Carolina, 2007.
520 $a Keywords. Invasive species, estuary, NERRS, Phragmites, GIS-based models, remote sensing, coastal resource management, geographic information processing.
520 $a Recently, research efforts have focused on the development and testing of geographic information processing (GIP) techniques to more effectively identify and monitor invasive plant species in coastal ecosystems. While these efforts are progressing, particularly with refinements in hyperspectral image processing, there remains a lack of practical, science-based tools for decision-making with respect to the monitoring and mitigation of invasive plant species. Therefore, a geographic information systems (GIS) model is proposed to quantify the probability of a future exotic plant invasion in a user-defined area of interest. The primary objective of this investigation is to present conceptual and technical descriptions of a proposed modeling approach for prediction of common reed (Phragmites australis) colonization in a managed coastal wetland environment. Successful validation and adoption of the model will promote continued discourse regarding the impact of invasive species in coastal ecosystems, while providing the management community with a valuable decision support tool. Three main chapters comprise this manuscript; Chapter 1 focuses on the evaluation of remote sensing data and techniques for directly identifying Phragmites australis in a coastal ecosystem; Chapter 2 describes proposed, GIS-based models for predicting Phragmites colonization and future growth projections; and Chapter 3 discusses the results of the compiled relative suitability index (RSI) compilation and growth models, and considers the key management implications of the investigation. In the absence of a universal eradication solution for the invasive species Phragmites australis, an integrated management approach that utilizes a suite of dynamic, geo-spatial techniques in concert with more traditional practices is ultimately recommended.
590 $a School code: 0202.
650 4 $a Biology, Ecology. $3 1017726
650 4 $a Environmental Sciences. $3 676987
650 4 $a Remote Sensing. $3 1018559
690 $a 0329
690 $a 0768
690 $a 0799
710 2 $a University of South Carolina. $3 1017477
773 0 $t Dissertation Abstracts International $g 68-08B.
790 $a 0202
790 1 0 $a Porter, Dwayne E., $e advisor
791 $a Ph.D.
792 $a 2007
856 4 0 $u http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=3280367