Computer Models for Vegetation Diversity Analysis

Computer Models for Vegetation Diversity Analysis

Bibliographic Details
Main Author: Ohanyan, Vahe A.
Language:English
Published: Ohio University / OhioLINK 2012
Subjects:
Bioinformatics
Ecology
Environmental Studies
Ecoinformatics
Diversity models
Vegetation ecology
Online Access:http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1328879870
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spelling ndltd-OhioLink-oai-etd.ohiolink.edu-ohiou13288798702021-08-03T05:47:17Z Computer Models for Vegetation Diversity Analysis Ohanyan, Vahe A. Bioinformatics Ecology Environmental Studies Ecoinformatics Diversity models Vegetation ecology <p>Ecoinformatics is considered a sub-discipline of bioinformatics and its goal is to create and expand software tools to manage, manipulate, store and distribute ecological information. Applications developed in ecoinformatics are quite practical in ecological data analysis, particularly in vegetation ecology. Vegetation ecologists are familiar with the challenges of analyzing large data sets, so ecoinformatics is a good tool to improve the problem-solving process. It is possible to automate much of the data analysis step and introduce higher levels of quality control. Software programs like R and Kepler are quite suitable for these purposes. Both are open source computer applications and may be used either alone or in an integrated manner. R is used by many biologists for statistical analysis, while Kepler is designed to automate the dataflow process. Both are userfriendly, and may be easily interfaced. These software applications have been used for certain types of diversity and community data managing projects. Here I present an example of models developed for specific types of data analysis in vegetation ecology.</p><p>In order to use the model developed for this project, one needs only supply a standard data set in spreadsheet format as input. The application automatically generates output with general necessary abundance estimates. Two models were developed for different types of plant community data. I expect a broad range for future applications of these models in both research and teaching.</p> 2012-04-18 English text Ohio University / OhioLINK http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1328879870 http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1328879870 unrestricted This thesis or dissertation is protected by copyright: all rights reserved. It may not be copied or redistributed beyond the terms of applicable copyright laws.
collection NDLTD
language English
sources NDLTD
topic Bioinformatics
Ecology
Environmental Studies
Ecoinformatics
Diversity models
Vegetation ecology
spellingShingle Bioinformatics
Ecology
Environmental Studies
Ecoinformatics
Diversity models
Vegetation ecology
Ohanyan, Vahe A.
Computer Models for Vegetation Diversity Analysis
author Ohanyan, Vahe A.
author_facet Ohanyan, Vahe A.
author_sort Ohanyan, Vahe A.
title Computer Models for Vegetation Diversity Analysis
title_short Computer Models for Vegetation Diversity Analysis
title_full Computer Models for Vegetation Diversity Analysis
title_fullStr Computer Models for Vegetation Diversity Analysis
title_full_unstemmed Computer Models for Vegetation Diversity Analysis
title_sort computer models for vegetation diversity analysis
publisher Ohio University / OhioLINK
publishDate 2012
url http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1328879870
work_keys_str_mv AT ohanyanvahea computermodelsforvegetationdiversityanalysis
_version_ 1719425261630390272

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