the convention on biological diversity ( cbd ) defines biodiversity as " the variety of life on earth and the natural patterns " . cbd has underlined the importance of abundant biodiversity in the sustainable use of natural resources . moreover , maintaining biological coexistence for all organisms on earth , including animals , plants , and microbes , is imperative for human welfare and quality of life . thus , many researchers use quantitative measures of biodiversity in an attempt to sustain and restore ecosystems . biodiversity is generally measured by statistical indices based on the emergence and/or existence of various organisms such as plants , animals , and microbes ; these indices can provide quantitative criteria with increased confidence for biodiversity . of the statistical indices , shannon - wiener index , species richness , and evenness the shannon - wiener index is based on information theory and is measured using the concept of entropy , and it is applied to estimate the degree of species diversity in a region . species richness and evenness measure the number of different species per sample and the relative abundance of the different species , respectively . for measuring biodiversity , there are a few non - commercial tools , such as the vegan package in r , estimates , and the web - based shannon entropy calculator ( http:// www.changbioscience.com/genetics/shannon.html ) . although they are highly useful , some of them are difficult and complicated for biologists to use , especially some programs involving r package . while the web - based tools are easy to use , they are not suitable for personal and/or big data sets . furthermore , some programs do not serve any function for long - term investigations of data sets using time - series analyses for biodiversity . we developed the vbioindex tool to aid scientists in evaluating the shannon - wiener index , species richness , and evenness . as vbioindex supports biodiversity analyses for a given period ( e.g. , for a month , quarter , or year ) , users can easily analyze a variety of biodiversity data while applying a time - series analysis . vbioindex supports four statistical indices - the shannon - wiener index , species richness , evenness , and the relative dominance of species - that are widely used as important criteria to evaluate ecosystems . the shannon - wiener index ( h ' ) was designed to predict the next letter of communication in a random set of data and to quantify entropy in terms of uncertainty or information content . it has been widely applied in a variety of fields , such as biology and ecology . h ' is measured using entropy with the proportion of individuals ( n ) for total emerged species ( s ) . pi = nii=1sni 
 h=-i=1spilogpi species richness ( dmg ) , known as margalef 's richness index , is a measure of the variety of species in a given area or sample , which is calculated based on emerged species ( s ) , and the individuals ( n ) of total emerged species . dmg = s-1logi=1sni species evenness ( e ) is the degree of the distribution of individual organisms among species , which is measured using h ' and the log of emerged species ( s ) . e = hlogs relative dominance ( rd ) is the frequency of individuals of a species , which generally presents the degree of dominance for a species as a percentage . rdi = nii=1sni100 vbioindex is implemented by clicking a few buttons , such as open , save , and some selectable radio buttons ( fig . an input data file is accepted as a tab - delimited file , labeled with the date , species name , and number of individuals ( fig . . the results of the four methods are graphically represented charts with a tab - delimited text output file ( fig . along with presenting these biodiversity indices , vbioindex allows time - series analyses at a monthly , quarterly , and yearly basis for all statistical methods , the functions of which are useful in analyzing long - term species diversity . vbioindex is programmed in java language ( higher than version 1.7 ) , and it can be used in all operating systems in which a java virtual machine has been installed . statistical indices evaluating ecology , such as the shannon - wiener index , species richness , evenness , and relative dominance , are considered important criteria to sustain and restore ecosystems . although there are a few programs for these indices , some programs are inconvenient to use and do not support various indices . we developed vbioindex , a user - friendly program that is capable of measuring the shannon - wiener index , species richness , evenness , and relative dominance . in addition , vbioindex offers options with which a user can analyze a variety of biodiversity data while applying a time - series analysis . vbioindex outputs a tab - delimited text file with visual charts and users can use the output text file with links to other statistical programs for a variety of ecological studies such as comparative analyses between many datasets .
biological diversity , also known as biodiversity , is an important criterion for measuring the value of an ecosystem . as biodiversity is closely related to human welfare and quality of life , 
 many efforts to restore and maintain the biodiversity of species have been made by government agencies and non - governmental organizations , thereby drawing a substantial amount of international attention . in the fields of biological research , 
 biodiversity is widely measured using traditional statistical indices such as the shannon - wiener index , species richness , evenness , and relative dominance of species . 
 however , some biologists and ecologists have difficulty using these indices because they require advanced mathematical knowledge and computational techniques . 
 therefore , we developed vbioindex , a user - friendly program that is capable of measuring the shannon - wiener index , species richness , evenness , and relative dominance . 
 vbioindex serves as an easy to use interface and visually represents the results in the form of a simple chart and in addition , vbioindex offers functions for long - term investigations of datasets using time - series analyses .