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Using Dispersion Statistic Scales as an Indicator for assessing the Biological

Diversity

ABSTRACT

Using statistical analysis is important for ecology

ministry, municipality organization, agriculture and

industrial sectors. Means, standard deviations, variance,

CV% and correlations were used as an indicator to

assess the biological diversity. SPSS and PAST

programs were used to analysis the data collected from

natural habitats. Based on the dispersion statistics

variance and CV% showed the most informative

measures. High values of CV% recorded the highest

biological diversity as well variance showed similar

findings. CV% affirmed that diversity increased with

increasing the elevation of regions above sea level. The

coefficient of variation is valuable since the standard

deviation of facts must always be known in the context

of the mean of the data. Correlation coefficient (R)

demonstrated the negative relationship between the

species grown at the wild habitats. Detrended

correspondence analysis (DCA) was used and

emphasized that there is wide diversity among the wild

type biological species. Statistical tools and its

applications are very important in evaluation the

biological diversity which helping in developing

conservation action plan for national, regional and

international level.

Keyword: ANOVA, Correlation, CV%, Jordan, PAST,

Standard deviation.

Advance Research Journal of Multi-Disciplinary Discoveries I Vol. 30.0 I Issue – I ISSN NO : 2456-1045

ISSN : 2456-1045 (Online)

(ICV-MCS/Impact Value): 63.78

(GIF) Impact Factor: 4.126

Publishing Copyright @ International Journal Foundation

Journal Code: ARJMD/MCS/V-30.0/I-1/C-5/OCT-2018

Category : MATHEMETICAL SCIENCE

Volume : 30.0 / Chapter- V / Issue -1 (OCTOBER-2018)

Journal Website: www.journalresearchijf.com

Paper Received: 29.10.2018

Paper Accepted: 07.11.2018

Date of Publication: 15-11-2018

Page: 26-31

Name of the Author (s):

Remal Shaher Al-Gounmeein1, Ibrahim M. Alrawashdeh2

1Mathematic Department, Science Faculty, AlHussein Bin Talal

University, Ma'an, Jordan.

2Biology Department, Science Faculty, AlHussein Bin Talal

University, Ma'an, Jordan.

Citation of the Article

Original Research Article

AL-Gounmeein RS; ALrawashdeh IM (2018) Using

Dispersion Statistic Scales as an Indicator for assessing the Biological Diversity ; Advance Research Journal of

Multidisciplinary Discoveries.30(5)pp. 26-31

Peer Reviewed , Open Access and Indexed Academic Journal ( www.journalresearchijf.com) Page I 26

http://www.journalresearchijf.com/



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III. RESULTS

In many ecological studies, a key metric for assessing stability has been based on the coefficient of variation (CV) of the

functional response, defined as the ratio of the standard deviation

to the mean response (Carnus et al., 2014). ANOVA for

biological diversity is illustrated in Table 1. Mean, standard deviation, variance, CV% and skewness for biological diversity

at four sites were shown in the Tables (2, 3, 4, 5). Analysis of

data showed that the range of variance was (0.17-110.41), (0.07-

0.46),(0.07-26.67) and (0.07- 64.29), for alshoubak/ Doshaq- fujij with elevation 1273m,Tafilah/ Qadesiah with elevation

1275m, alshoubak/ Abu-Eid with elevation 1420m, alshoubak/

Aljhair with elevation1554m, respectively Table (2, 3, 4 and 5)

with highest value (110.41) recorded to Hordeum sp. at alshoubak district (1273 m), Artemisia herba alba 0.46 at

Tafilah/ Qadesiah (1275m), Achillea santolinea 26.67 in

alshoubak/ Abu-Eid with 1420m, and 64.29 was recorded for

Lasiopogon muscoides at 1554m alshoubak/ Aljhair. The range of coefficient of variation registered for alshoubak/Doshaq-fujij

with elevation 1273m was 105-280, Tafilah/Qadesiah with

elevation 1275m was 85-388, alshoubak/Abu-Eid with elevation

1420m was 86-388, alshoubak/ Aljhair with elevation1554m was 100-385, respectively Table (2, 3, 4 and 5), where the highest

values recorded for Hordeum vulgare., Artemisia herba alba,

Achillea santolina and ( Lasiopogon muscoides, Avena sterilis ;

Sinapis arvensis), respectively Tables ( 2,3,4 and 5). On the hand, the skewness for alshoubak/ Doshaq- fujij with elevation

1273m was ranged 0.44-2.62,Tafilah/Qadesiah with elevation

1275m was0.21-3.13, alshoubak/Abu-Eid with elevation 1420m

was 0.89-3.13, alshoubak/ Aljhair with elevation1554m was 0.85-2.98, respectively Table (2, 3, 4 and 5). The association

among biological species illustrated at Table 6. In the Table 6,

Negative association was set up between plant individuals. For

example Scorzonera judaica species showed negative relation with Centaurea sp., Hordeum vulgare, Anabasis syriaca,

Artemisia herba-alba Asso., Hordeum sp., Noaea mucronata,

Anthemis tinctoria, and Sinapis arvensis. Positive correlation

was found between Scorzonera judaica and Achillea santolina, Lasiopogon muscoides and Avena sterilis (Table 6). Correlation

(R) among studied biological samples was found in the Table (6

and 7) and (Figure 1 and 2). Figure 1 showed that diversity

increased with increase the biological samples. Figure 2 explain that the distribution of biological diversity patterns was scattered

with grouping some of associated biological species based on the

Detrended correspondence analysis. Highly significant


I. INTRODUCTION

Statistic is a science that assist in summarizing data, familiar terms such as data Mean, variance. These terms as well

detrended correspondence used to relate species communities at the

level of plants and animals to known variation in the environment.

The one-way ANOVA problem with unequal variances is a simplification of the well-known Behrens-Fisher problem, which is

one of the oldest and most exciting problems in statistics (Sadooghi-

Alvandi et al., 2102). Analysis of variance is mainly valuable

implement for analyzing highly planned experimental data in agriculture, animals and humans located at different habitats. Also,

help in understanding of ecosystem changes which is needed for

ecologists that supplies society with the knowledge necessary for

judicious management or action plan of the ground and its biological resources. Correlations measure the strength of linear

association between two continuous variables. Sari et al., (2017)

used the Pearson correlation coefficients to estimate the correlation

between cherry tomato variables. The coefficient of variation (CV) is a unit less measure typically used to evaluate the variability of a

population relative to its standard deviation and is normally

presented as a percentage (Canchola et al., 2017). Carnus et al.,

(2014) stated that to date, ecological studies that aim to measure stability in ecosystem function across a range in diversity have

almost universally used the coefficient of variation (CV, the ratio of

standard deviation (SD) of functional response to its mean), or its

inverse 1/CV, in reaching conclusions. Coefficient of variation was intensively used in many previous studies such as diversity of

physic nut (Shabanimofrad et al., 2011). Lepš, (2004) measured the

variability by the coefficient of variation between years, from the

fifth to the eighth year of the experiment. Detrended correspondence along with other correspondence analysis were effectively used to

examine society constitution and its fundamental environmental

source, as well as several marine studies. Ayoub-Hannaa et al.,

(2013) stated that detrended correspondence analysis (DCA) is a simple multivariate technique for arranging for species and samples

along environmental gradients was used for reconstructing

palaeoecology patterns and biostratigraphy. Detrended

correspondence analysis (DCA), an ordination technique used to explain patterns in complex data sets, arranged the sample sites

along an ordination axis that explained 76% of the variation in the

phytoplankton abundance data matrix (Garono et al., 1996). Gomaa,

(2012) said that by using ten quadrats (1x1) m per stand a total of 71 species belonging to 22 families and 61 genera were observed. On

the other hand, he used detrended correspondence analysis (DCA)

and showed that these groups are clearly distinguished by the first

two DCA axes. ANOVA as a technique of analyzing highly planned data by decomposing variance into different sources, and comparing

the explained variance at each level to what would be expected by

chance alone. Because in adequate information was published about

the biological diversity of studied areas under this work and mainly Scorzonera judaica species. The aim of this study was focusing on

application of statistical tools and techniques in analysis of

biological diversity at the wild habitats.

II. MATERIALS AND METHODS

Data were obtained based on the Quadrate - transects technique for assessing the biological diversity at four locations in

alshoubak and one at Altafilah areas. These areas were located in

the southern part of Jordan. The study area is characterized by dry

climate with hot summer and cool winter. Sixty quadrates (1x1) meter were used along three randomly transects overall studied

areas. The data were inserted on excel sheet then transferred into

programs of analysis.

III. DATA ANALYSIS

Means, standard deviations, variance and correlations

calculated according to formulas outlined by (Steel and Torrie, 1980 and Hammer et al., 2001). Detrended correspondence was analyzed

using the PAST software program ver. 2.18c (Hammer et al., 2001).

Correlation was obtained through using SPSS, V. (11.0), software.

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relationship was found between certain biological species such as Lasiopogon muscoides and Avena sterilis (1.00) it seems more

associated and those favorite the same niches and Anthemis tinctoria and Hordeum vulgare (0.79); Hordeum vulgare and Anabasis syriaca

(0.76) Table 7.

Table 1: One-way ANOVA

Sum of square df Mean square F P

Between groups 88.149 11 8.0135 1.447 0.147

Within groups 3921.12 708 5.5383

Total 4009.12 719

Table 2: Mean, standard deviation, variance and skewness for biological diversity at (1273) meter elevation at

al shoubak sub district.

Scorzonera judaica Centaurea sp. Anabasis syriaca Hordeum sp. Hordeum vulgare

Mean± standard deviation

0.6±0.63 0.4±1.06 0.2±0.414 4.13±10.51 1.00±2.8

Variance

0.40 1.11 0.17 110.41 7.86

Skewness

0.44 2.62 1.35 1.94 2.36

CV%

105 265 207 254 280

Table 3: Mean, standard deviation, variance and skewness for biological diversity at (1275 ) meter elevation at

al Tafilah sub district.

Scorzonera judaica Artemisia herba-alba Asso. Noaea mucronata Hordeum sp.


0.267±0.46 0.80±0.68 0.13±0.35 0.067±0.26

Variance

0.21 0.46 0.12 0.07

Skewness

0.95 0.21 1.94 3.13

CV%

172 85 269 388

Table 4: Mean, standard deviation , variance and skewness for biological diversity at (1420) meter elevation at

al alshoubak sub district.

Scorzonera judaica Noaea mucronata Artemisia herba-alba Asso. Achillea santolina Centaurea sp.


0.20±0.414 0.27±0.59 0.93±0.80 1.33±5.16 0.07±0.26

Variance

0.17 0.35 0.64 26.67 0.07

Skewness

1.35 1.84 0.89 3.13 3.13

CV%

207 218 86 388 371

Table 5: Mean, standard deviation , variance and skewness for biological diversity at (1554) meter elevation at

al alshoubak sub district.

Scorzone

ra

judaica

Artemisia

herba-

alba

Asso.

Hordeum

sp.

Centaurea

sp.

Anthemis

tinctoria

Achillea

santolina

Lasiopog

on muscoides

Avena

sterilis

Sinapis

arvensis


0.29±0.47 0.86±0.86 0.64±2.41 1.00±1.62 0.21±0.58 1.79±6.68 2.14±8.02 0.07±0.27 0.07±0.27

Variance

0.22 0.75 5.79 2.62 0.34 44.64 64.29 0.07 0.07

Skewness

0.85 0.91 2.98 1.42 2.23 2.98 2.98 2.98 2.98

CV%

162 100 377 162 276 373 375 385 385

Analysis of data showed that the range of variance was (0.17-110.41), (0.07-0.46),(0.07-26.67) and (0.07- 64.29), for alshoubak/ Doshaq- fujij with elevation 1273m,Tafilah/ Qadesiah with elevation 1275m, alshoubak/ Abu-Eid with elevation 1420m, alshoubak/ Aljhair with

elevation1554m, respectively Table (2, 3, 4 and 5) with highest value (110.41) recorded to Hordeum sp. at alshoubak district (1273 m),

Artemisia herba alba 0.46 at Tafilah/ Qadesiah (1275m), Achillea santolinea 26.67 in alshoubak/ Abu-Eid with 1420m, and 64.29 was




Table 6: Measure of association between Scorzonera judaica and plant species grown within natural habitats of

Alshoubak and Altafilah areas.

Species association R R square

Scorzonera judaica* Centaurea sp -.175 .031

Scorzonera judaica* Hordeum vulgare -.157 .025

Scorzonera judaica* Anabasis syriaca -.138 .019

Scorzonera judaica* Artemisia herba-alba Asso. -.121 .015

Scorzonera judaica* Hordeum sp. -.115 .013

Scorzonera judaica* Noaea mucronata -.102 .010

Scorzonera judaica*Achillea santolina .074 .006

Scorzonera judaica* Anthemis tinctoria -.121 .015

Scorzonera judaica*Lasiopogon muscoides .166 .027

Scorzonera judaica* Avena sterilis .166 .027

Scorzonera judaica* Sinapis -.089 .008

Table7: Correlation coefficient among biological diversity of plants using SPSS program.

Species

A B C D E F G H I J K L

Scorzoner

a judaica

Centaure

a sp.

Anabasi

s syriaca

Hordeu

m sp.

Hordeu

m

vulgare

Artemisi

a herba-

alba

Asso.

Noaea

mucronat

a

Achillea

santolin

a

Anthemi

s

tinctoria

Lasiopo

gon

muscoi

des

Avena

sterilis

Sinapis

arvensis

A Scorzonera

judaica 1

B

Centaurea

sp.

- 0.175 1

C Anabasis

syriaca 0.175 -0.081 1

D Hordeum

sp. - 0.138 0.36 0.369* 1

E Hordeum

vulgare - 0.121 0.062

0.767*

* 0.604** 1

F

Artemisia

herba-alba

Asso.

- 0.115 0.015 0.107 0.064 0.004 1

G Noaea

mucronata - 0.102 0.052 - 0.065 0.045 -0.050 -0.057 1

H Achillea

santolina 0.074 0.264* - 0.042 0.040 -0.032 -0.023 -0.053 1

I Anthemis

tinctoria -0.121 0.173

0.498*

* 0.604** 0.794** -0.153 -0.050 0.265* 1

J

Lasiopogo

n

muscoides

0.166 0.085 - 0.030 0.005 -0.023 0.061 -0.037 -0.024 -0.023 1

K Avena

sterilis 0.166 0.085 - 0.030 0.005 -0.023 0.061 -0.037 -0.024 -0.023 1.00** 1

L Sinapis

arvensis - 0.890 0.477** - 0.030 0.029 -0.023 -0.113 -0.037

0.617*

* 0.436** -0.017

-

0.017 1




Figure 1: Correlation between studied of herbaceous plant

samples using PAST program.

Figure 2: Detrended correspondence with (95% ellipses and convex

hulls) among different plant samples using PAST program.

IV. DISCUSSION

In our study high values of variance were recorded for

biological species with high number of individuals compared with low number of other species. Our result were in agreement with

finding of Katsanevakis, (2006) who was reported that the large

standard deviation resulted mainly from the variance in densities of

small individuals and especially those of the 3 to 5 m zone. The variance in densities of large individuals was much lower and their

number was estimated to be 4146 ± 1405 individuals. CV has been

effectively used in the recent and past in determining the genetic

diversity and in identifying regions of high diversity. CV% showed highest value of species abundance and the presence of biological

species is more related with region elevation. The CVspecies is

often not constant and decreases with species abundance, depending

on how the variance is scaled with the mean (Lepš, 2004). Reed-Dustin et al., (2012) ) reported that the relationship between native

species richness and the coefficient of variation was not statistically

significant (R2=0.43; p-value=0.16) and therefore did not support

our hypothesis that native plants diversity in wetland prairies increases with topographic variation. To estimate the Pearson

coefficients of correlation between cherry tomato variables with a

95% confidence interval amplitude equal to 0.4, it is necessary to

sample 275 plants in the 250m² greenhouse and 200 plants in the 200m2 greenhouse (Sari et al., 2017). Detrended correspondence

was used to show the distribution of biological patterns within

restricted areas. In this research, DCA assessed that the Scorzonera

judaica species was completely differ from the rest biological species which indicate it has diverge genetic makeup. The DCA

ordination analysis showed differences between the studied areas.


Gomaa, (2012) found that the studied biological species are

clearly distinguished by the first two DCA axes. DCA is a highly efficient technique for studying the environmental, taxonomic

and biomass relationships.

V. CONCLUSION

1. Variance measurement assessed that diversity was

increased with increased the sit elevation.

2. CV% was highest affirmed the variability

associated with elevation. 3. Correlation (R) demonstrated that negative

relationship appeared between biological species .

4. Using statistical tool help in know the factors

effect on the distribution of biological diversity such as climate change, human interfering and

unexpected disasters.

5. Detrended correspondence analysis is an effective

technique that can be used in demographic and

environmental studies.

REFERENCES

[1]. Ayoub-Hannaa W, Huntley JW, Fürsich FT.

Significance of Detrended Correspondence Analysis (DCA) in palaeoecology and iostratigraphy: A case

study from the Upper Cretaceous of Egypt. Journal of

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*****


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