research article evaluating insects as bioindicators of...

Research ArticleEvaluating Insects as Bioindicators of HeavyMetal Contamination and Accumulation nearIndustrial Area of Gujrat Pakistan

Iqra Azam1 Sumera Afsheen1 Ahmed Zia2 Muqaddas Javed3 Rashid Saeed4

Muhammad Kaleem Sarwar1 and Bushra Munir5

1Department of Zoology Institute of Life Sciences University of Gujrat Punjab 50700 Pakistan2National Insect Museum National Agriculture Research Centre Islamabad Pakistan3Department of Statistics University of Gujrat Punjab 50700 Pakistan4Department of Environmental Sciences Institute of Life Sciences University of Gujrat Punjab 50700 Pakistan5Department of Applied Chemistry and Biochemistry Government College University of Faisalabad Punjab 38000 Pakistan

Correspondence should be addressed to Sumera Afsheen sumeraafsheenuogedupk

Received 12 February 2015 Revised 16 April 2015 Accepted 16 April 2015

Academic Editor Chong-Jian Tang

Copyright copy 2015 Iqra Azam et al This is an open access article distributed under the Creative Commons Attribution Licensewhich permits unrestricted use distribution and reproduction in any medium provided the original work is properly cited

To study the accumulation and contamination of heavy metals (ie Cd Cr Cu Ni and Zn) in soil air and water few insect specieswere assayed as ecological indicators Study area comes under industrial zone of district Gujrat of Punjab Pakistan Insects usedas bioindicators included a libellulid dragonfly (Crocothemis servilia) an acridid grasshopper (Oxya hyla hyla) and a nymphalidbutterfly (Danaus chrysippus) near industrial zone of Gujrat Accumulation of Cd was highest in insect species followed by CuCr Zn and Ni at 119901 lt 005 Hierarchical cluster analysis (HACA) was carried out to study metal accumulation level in allinsects Correlation and regression analysis confirmed HACA observations and declared concentration of heavy metals abovepermissible limits Metal concentrations in insects were significantly higher near industries and nallahs in Gujrat and relativelyhigher concentrations of metals were found in Orthoptera thanOdonata and LepidopteraThe total metal concentrations in insectswere pointed significantly higher at sites S3 (Mid of HalsiNala) S9 (End of HalsiNala) and S1 (Start of HalsiNala) whereas lowestvalue was detected at site S6 (Kalra Khasa) located far from industrial area HACA indicates that these insect groups are potentialindicators of metal contamination and can be used in biomonitoring

1 Introduction

Natural ecosystems all over the world have been adverselyaffected by human interventions [1] Modern farming indus-trialization and increased vehicular use have led to high con-centrations of heavy metals such as lead nickel chromiumcadmium aluminum mercury and zinc in the environ-ment [2] These toxic heavy metals are regularly gettinginto air water and soil thereby becoming part of naturalbiogeochemical cycle [3] Insects have strong relationshipwith ecology and are popularly used as bioindicators sincelong time [4] Acute and chronic effects of heavy metalson various insects are frequently reported in the form of

growth inhibition developmental abnormalities reducedreproduction and decreased hatchability [5]

Among aquatic insects dragonflies are taken as beingmost sensitive to habitat disturbance [6] Their presence inany water body confirms its synthetic pollution-free status[7] Ecologically they are good indicator of the condition ofterrestrial as well as aquatic ecosystems [8 9] Butterflies andgrasshoppers also have ecological fidelity and are sensitiveto environmental changes and quality According to Chenet al [10] these insects have been successfully used asbioindicators for environmental pollution and heavy metalscontaminations near industrial states and even within urbanareas

Hindawi Publishing CorporationBioMed Research InternationalVolume 2015 Article ID 942751 11 pageshttpdxdoiorg1011552015942751

2 BioMed Research International

Pakistan

Punjab

Gujrat

Gujrat

32∘29

9984000998400998400N

32∘30

9984000998400998400N

32∘31

9984000998400998400N

32∘32

9984000998400998400N

32∘33

9984000998400998400N

32∘29

9984000998400998400N

32∘30

9984000998400998400N

32∘31

9984000998400998400N

32∘32

9984000998400998400N

32∘33

9984000998400998400N

74∘49984000998400998400E74

∘39984000998400998400E 74

∘59984000998400998400E 74

∘79984000998400998400E74

∘69984000998400998400E

74∘49984000998400998400E74

∘39984000998400998400E 74

∘59984000998400998400E 74

∘79984000998400998400E74

∘69984000998400998400E

End of HalsiNala

Near Chenab River

Kathala ChenabKalra Punwan

Mid of HalsiNala

Kalra Khasa

Start of HalsiNalaSmall Industrial Area

0 25125 100(km)

Sites

7550

Kalra Kalan

N

Chenab_river

Figure 1 Map showing sampling sites (Arc GIS 93)

The reasons for using these insect species as indicatorare follows (1) use of several different taxa of differenthabitat gives more robust results (2) a quantitative indicatorvalue needs to be associated with the bioindicators (3)there is similarity between different landscape features (4)there is comparison of community (5) these taxa can bereliably identified sampled and quantified and (6) morethan one family surely indicate species richness of an order[11] At landscape level strong correlation is found amonggrasshoppers (herbivore) and butterflies (nectivore and her-bivore) Furthermore for bioindication of ecological changewe used aquatic insect dragonfly (Order Odonata) Theyare considered as best ecological indicator in water andriparian systems They give a rapid and sensitive response toaccumulation of heavy metals [12]

Gujrat is an important industrial area of Punjab provinceof Pakistan It is business bay for ceramics fan furnitureand leather industry Qadir et al [13] reported more than1000 cottage-level to large-scale industrial units from thisdistrict In recent past structure ground water and landscapeof Gujrat have been reported to be rapidly degraded dueto industrialization increased urbanization and modernagricultural activities leading to injudicious use of pesticidesand fertilizers [14] Keeping in view environmental andhealth concerns due to increased heavymetal contamination

present study was designed to investigate level of heavymetal contamination in district Gujrat by using insects asbioindicators

2 Materials and Methods

Survey to study heavy metal contamination was carried outduring September 2013 to August 2014 in nine localities(Start of HalsiNala (S1) Kalra Punwan (S2) Mid of HalsiNala(S3) Small Industrial Area (S4) Kalra Kalan (S5) KalraKhasa (S6) Kathala Chenab (S7) Near Chenab River (S8)and End of Nala (S9)) of Tehsil Gujrat (Figure 1) Detailsregarding coordinates and vegetation cover at each samplingsite are shown inTable 1 Siteswere selected at nearest possibledistance to the functioning industrial units Three insectsgroups were chosen to be used as bioindicators It included alibellulid dragonfly (Crocothemis servilia) a nymphalid but-terfly (Danaus chrysippus) and an acridid grasshopper (Oxyahyla hyla)These were collected from rice and wheat crops onquarterly basis for a period of one year Three specimens ofeach group were recorded from each site so the total numberof specimens (sample size) becomes twenty-seven for eachspecies (Table 2) Soil and plant samples were also collectedfrom same sites and stored in sterilized polythene bags untilreaching laboratory Represented specimens of each group

BioMed Research International 3

Table1Geographicallocationandvegetatio

ntype

ofsamplingsites

Sitessele

cted

for

sampling

Site1

Starto

fHalsiN

ala

Site2

Kalra

Punw

anSite3

Mid

ofHalsiN

ala

Site4

SmallInd

ustrial

Area

Site5

Kalra

Kalan

Site6

Kalra

Khasa

Site7

KathalaC

henab

Site8

near

theC

henab

River

Site9

Endof

Nala

Latitud

e32∘

331015840

285810158401015840

N32∘

321015840

536410158401015840

N32∘

331015840

90210158401015840

N32∘

331015840

5870N

32∘

321015840

467310158401015840

N32∘

321015840

449810158401015840

N32∘

311015840

150710158401015840

N32∘

291015840

25771210158401015840

N32∘

311015840

77310158401015840N

Long

itude

74∘

51015840560610158401015840

E74∘

51015840521810158401015840

E74∘

51015840215710158401015840

E74∘

51015840248010158401015840

E74∘

5101584025010158401015840

E74∘

51015840384310158401015840

E74∘

6101584055310158401015840

E74∘

510158403019

9210158401015840

E74∘

51015840398510158401015840

EVe

getatio

nRice

Rice

Rice

Rice

Wheat

Wheat

Wheat

Wheat

Rice


Table2Samplingtim

ealong

with

temperaturehum

idityand

typeso

finsectrecorded

Season

Activ

eseason

Mod

erately

activ

eseason

Mon

th(2013-14)

May

2014

June

2014

July

2014

Aug

2014

Sept

2013

Oct

2013

Nov

2013

Dec

2013

Jan

2013

Feb

2013

Mar

2013

April

2013

Type

ofcrop

s(vegetation)

Rice

Rice

Rice

Rice

Rice

Rice

Rice

Wheat

Wheat

Wheat

Wheat

Wheat

Temperature

(Celsiu

s)33∘

C45∘

C40∘

C32∘

C31∘

C28∘

C25∘

C20∘

C21∘

C25∘

C26∘

C28∘

C

Dew

point

temperature

TD(C

elsiu

s)21∘

C32∘

C28∘

C20∘

C19∘

C17∘

C14∘

C9∘C

10∘

C14∘

C15∘

C17∘

C

Relativeh

umidity

(119891)p

ercent

4926

4902

5084

4903

4880

5123

5053

4922

4955

5053

5077

5123

Typeso

finsects

collected

Butte

rfly

Butte

rfly

grasshop

per

Butte

rfly

grasshop

per

Grassho

pper

Grassho

pper

dragon

flyGrassho

pper

dragon

flyGrassho

pper

dragon

flyBu

tterfly

Butte

rfly

Butte

rfly

Butte

rfly

Butte

rfly

grasshop

pers


were sent to National Insect Museum NARC Islamabad fortaxonomic confirmation

Gujrat is the most important industrial district of PunjabHere the main sources of pollution in this region includesmoke from chimneys sewage water released into ldquoHalsi-Nalardquo and toxic waste dump sites Contaminated water fromldquoHalsiNalardquo is used for irrigation purposes in nearby fieldsthat ultimately affect crops leading to heavy metal accumula-tion Insects were collected from nine sites of industrial area(32∘331015840285810158401015840N 74∘51015840560610158401015840E to 32∘31101584077310158401015840N 74∘51015840398510158401015840E)for the assessment of heavy metals (Cu Zn Cd Ni and Cr)

Insects were mechanically dried in oven weighed onmicrobalance and digested in a mixture of supra puregrade nitric acid and perchloric acid mixed 4 1 Digestswere analyzed for metal contents using atomic absorptionspectrophotometer in an air-acetylene flame for zinc andcopper and in a PU-93 090X graphite furnace for copperchromium cadmium nickel and zinc

Descriptive statistics analysis of variance (one-way)ANOVA bivariate correlation and regression analysis weremade on recorded data by testing significance differencesat 119901 lt 005 using SPSS 160 Site dependent statisticaldifferences between mean concentrations of heavy metalsin each of the insect taxa were examined using descriptivestatistics Hierarchical cluster analysis (HACA) based onagglomerative statistics using Wardrsquos Method was calculatedfor concentration of heavy metals at each of the samplingsites

3 Results and Discussion

All studied sites generally showed remarkable species basedvariations in metal concentrations (Figure 2) Highest metalconcentration was observed in the Danaus chrysippus fromldquoEnd of Nalardquo Significant site-based differences in levels ofcontamination were observed in the mean concentration ofheavy metals at each site however it varied up to threefoldbetween examined species (Table 3) Lowest heavy metalconcentration was seen in Danaus chrysippus specimensrecorded from Kalra Punwan (S2) Apparent species depen-dent differences in metal pollution gradient were found ineach examined species All sampled soils were found tobe slightly acidic showing pH around neutrality (Table 4)Larger differences were however observed for organic mattercontents and available phosphorus (Table 9) Descriptivestatistics for soluble salts and other properties of watersamples taken from nine sites is shown in Table 5

Nonparametric test was also carried out for obtaineddata of this study Two-independent-sample tests by Mann-Whitney test for two values and 119870 independent tests byKruskal-Wallis test and Jonckheere-Terpstra test were done tocompare means of data The distribution as shown in Table 7indicates that season site crop and HMG show insignificantresults while metals show significant results at 119901 lt 005 Itwas thus likewise accepted that season site crop and HMGhave equal effect on accumulation of heavy metals in insectrsquosbody On the other hand type of metal does not show equaleffect and gave significant results at 119901 lt 005

Variation within each parameter of soil and water showedtheir effect on each other (Table 7) EC OM AK andS showed significant results in soil at 119901 lt 005 whileAP displayed insignificant results and hence pH and APshowed equal effect In water parameters all factors displayedsignificant results at 5 level of significance

Correlations betweenmetals were also studied and foundpredominantly positive in the case of Cd and Cr (Table 8)However it was observed to be positive as well as negativein case of Ni Zn and Cu Zn concentrations were species-specific and correlation with Zn Ni level in humus layer wasstatistically insignificant Significant correlation was foundbetween Cd Zn and Cr in O hyla hyla Cd Zn and Cr inC servilia (119901 lt 005) But strongly positive relationship wasobserved between Zn and Cr in D chrysippus and Zn Crand Cd in O hyla hyla Similarly in C servilia strong positiverelationship was seen between Cr andCu Cr and Zn Cd andNi Body level of Cr Cd correlated negatively with those of Niand Cu inO hyla hyla andD chrysippus species except for Cservilia

Table 11 explains the regression analysis of heavy metalsgroup (O hyla hyla C servilia and D chrysippus) usingcopper (Cu) chromium (Cr) and cadmium (Cd) as depen-dent for each insect group By critically evaluating Table 11 itis concluded that the model of O hyla hyla which containcopper (Cu) and chromium (Cr) as dependent is insignifi-cant and the independent variables moderately explain thevariation of dependent variables Whereas the model of Ohyla hyla which contain cadmium as dependent variable andnickel (Ni) zinc (Zn) chromium (Cr) and copper (Cu) asindependent is significant independent variables can explain88 variation of dependent variable and all 120573 are significantSo overall we can conclude that the model which containscadmium as dependent variable is suitable to explain metaltoxicity in O hyla hyla

The models of C servilia which contain copper (Cu)and chromium (Cr) as dependent are insignificant and theindependent variables moderately explain the variation ofdependent variables whereas the model of C servilia whichcontain cadmium (Cd) as dependent variable and nickel (Ni)zinc (Zn) chromium (Cr) and copper (Cu) as independent issignificant Independent variables can explain 88 variationof dependent variable and all 120573 are significant So overallwe can conclude that the model which contains cadmium asdependent variable is suitable to explain the C serviliametaltoxicity

In regressionmodel for third group (D chrysippus) whichcontain copper (Cu) and chromium (Cr) and cadmium (Cd)as dependent all are insignificant By critically observingvalues of all 120573 we conclude that overall model is weak Hencecopper (Cu) and chromium (Cr) and cadmium (Cd) cannotbe used to represent the metal concentrations of all othermetals Our results of predictive model clearly demonstratedthat these metals have different anthropogenic source andtheir concentrations are not explained relative to each other

Hierarchical agglomerative cluster analysis (HACA) wasalso evaluated to assess concentration of heavy metals inurban soils and to check environmental quality for each dataset (three insect taxa) multivariate cluster analysis using SPSS


Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s

SiteS9S8S7S6S5S4S3S2S1

060

040

020

000

Cd

(a)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Cu

(b)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


1500

1000

500

000

Ni

(c)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Zn

(d)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


2000

1500

1000

500

000

ButterflyDragonflyGrasshopper

HMG

Cr

(e)

Figure 2 Mean values and standard deviations of metal concentrations in three insect taxa


Table 3 Mean concentrations of metals (mgL) plusmn SD recorded in three insect taxa

Site Number O hyla hyla C servilia D chrysippusStart of HalsiNala 5 2596 plusmn 3979 2961 plusmn 4321 1520 plusmn 1850Kalra Punwan 5 4574 plusmn 5200 2920 plusmn 4380 1180 plusmn 1590Mid of HalsiNala 5 5939 plusmn 8300 3388 plusmn 4457 3470 plusmn 6007Small Industrial Area 5 4698 plusmn 5760 3133 plusmn 4214 1733 plusmn 1907Kalra Kalan 5 3930 plusmn 4550 3512 plusmn 4474 3755 plusmn 5905Kalra Khasa 5 4592 plusmn 5087 3395 plusmn 4497 1550 plusmn 1845Kathala Chenab 5 4827 plusmn 5656 3001 plusmn 4381 1313 plusmn 1926Near the Chenab River 5 4525 plusmn 5501 4354 plusmn 5199 3741 plusmn 5232End of Nala 5 4304 plusmn 5255 3505 plusmn 4405 5920 plusmn 7660

Table 4 Descriptive statistics for pH EC OM and other properties in urban soil of nine selected sites

Soil parameters 119873 Minimum Maximum Mean Std Deviation SkewnessStatistic Std error

pH 9 430 760 70444 103816 minus2901 717Electrical conductivity msdotmohscm 9 220 1132 38556 286815 2733 717Organic matter age 9 19 76 4344 21858 185 717Available Phosphorous (ppm) 9 300 1100 63333 308221 256 717Available potash (ppm) 9 6000 22000 128331198642 6129029 228 717Saturation age 9 3800 7000 548889 1432170 minus275 717

160 was applied to ascertain similarity between the sitesMetal concentration in three insect taxa (O hyla hyla Cservilia and D chrysippus) showed significant differences inaccordance with land type at each site Sites located withinindustrial area represented higher values of metals in insectsthan in sites far from them Heavy metals presented majorvalues in S5 (Small Industrial Area I) with industrial area(Table 6) Lowest value was detected in S6 (Kalra Khasa)located far from industrial area Cluster analysis was appliedto the values of metal concentration for three insect taxaat nine sites S1 located at the start of Halsi Nala showeddifferent pattern of concentration of metals CA groupedsampling sites into clusters (called zones in this study) on thebasis of similarities within a zone and dissimilarities betweendifferent zones Result of CA helped in interpreting the dataand indicating pattern of similar objects Wardrsquos methodwas used as a clustering technique to identify the zones indata and square Euclidean distance was used as a distancematrix

Three zones were identified using CA in each of theinsect taxa (Figures 3 4 and 5) Zone 1 consisted of highlypolluted sites namely 1 and 3 (Start of HalsiNala and Mid ofHalsiNala) This zone was restricted to those places that werein close proximity to industrial stagnant waters and seasonalnallahs receiving large volumes of effluents and sewagewaste throughout the year Mid of HalsiNala had stagnantwater in which pollutants from urban industrial waste andagricultural runoff during monsoon are discharged It islikely that seepage and infiltration of pollutants from nearbyrunning HalsiNala affect the quality and purity of waterand soil at this site Generally level of measured heavymetals was low in this zone in comparison to sites 1 3and 9

31 Discussion Insects are typically the overwhelminglydominant invertebrate faunal group and extensively used inbiomonitoring and bioassessment programs throughout theworld Metals detected in our examined species are as aresult of industrial effluents agricultural runoff vehicularsmoke domestic and sewage wastes and use of fertilizers Asthese metals are persistent and cannot be degraded by insectmetabolism hence these are accumulated at upper trophiclevel

Analytical results obtained during present study are pre-sented for all studied elements season insect taxa (species)and sites As can be expected insignificant differences wereobserved in metal concentration for all investigated sampledsites In grasshoppers as a polyphagous and omnivorousinsect relatively higher contents of heavy metals were foundat site ldquoStart of HalsiNalardquo and ldquoMid of HalsiNalardquo thatwere nearer to the industrial area As a predator dragonflies(C servilia) also had higher contents of heavy metals as itconsumes many other insects of that area and thus accumu-lates high concentration of metals from aquatic environmentcompared to other two insect groups studied Butterflies(D chrysippus) being nectivorous comparatively showedless concentration of heavy metals as compared to otherinsect taxa studied These results are in accordance with theobservations of Li et al [15] who point out that some metalscontamination like Cd andNi decreases with increased tropiclevels

In the current study all the three insect taxa clearly showsite and species dependent metal accumulation patterns forCd Ni Cr Zn and Cu Significantly elevated concentrationswere found for Cd Cr and Cu in ldquoMid of HalsiNalardquo gt ldquoEndof Nalardquo gt ldquoEnd of Nalardquo and it thus confirms the expectationthat animal bodyrsquos burden reflects site pollution (119901 lt 005)


Table 5 Descriptive statistics for soluble salts and other properties in water of nine selected sites

Water parameters 119873 Minimum Maximum Mean Std Deviation SkewnessStatistic Std error

Soluble salts Tss (ppm) 9 50500 102400 862891198642 14747241 minus2017 717Ca+ + Mg+ 9 500 800 63333 103078 905 717Na+ 9 05 467 21967 125510 286 717HCO

3

minus 9 450 850 66667 139194 minus263 717Clminus 9 50 200 12778 61802 092 717Sodium absorption ratio (SAR) 9 05 281 13800 86757 206 717

(A) Grasshoppers

Dendrogram using Ward methodRescaled distance cluster combined

Label Num0 5 10 15 20 25

S2S6S8S4S7S5S9S3S1

268475931

H I E R A R C H I C A L

C A S E

C L U S T E R A N A L Y S I S

Figure 3 Dendrogram of the cluster analysis (using Wardrsquos Method) applied for metal concentration in grasshoppers (O hyla hyla) at ninesites

Table 6 Test statistics for equal effect of each factor on heavy metalaccumulation

Group Test Statistics SignificanceSeason Mann-Whitney test 552200 0823

lowastlowast

Site Kruskal-Wallis test 27 0952lowastlowast

Jonckheere-Terpstra test 12053500 0152

Crop Mann-Whitney test 5522 0823lowastlowast

HMG Kruskal-Wallis test 3225 0521lowastlowast

Jonckheere-Terpstra test 10216500 0868lowastlowast

Metal Kruskal-Wallis test 164050 0000lowast

Jonckheere-Terpstra test 453900 0000lowast

lowastSignificant at 5lowastlowastSignificant at 1

Less contrasting differences were found for Ni while Znranges were not significantly different between all sites exceptat site 3 It might be assumed that in insect metabolism thereare physiological mechanisms which aid in regulations ofmetal ions concentrations and prevent toxic levels

For each group of insect species site and species depen-dent differences are recorded quite high which can be usedas bioindicator of heavy metal stress at particular site andin particular species Sampling localities found in vicinityof urban areas are suffering with heavy load of metal stresswhich ultimately results in higher concentrations of Cd NiCr Zn and Cu as compared to less polluted domains side by

Table 7 Variations observed within group in soil parameters

Group 1 Group 2 Statistics SignificanceSoil parameters

EC 90 0004lowast

OM 000 0000lowast

pH AP 380 0863AK 000 0000

lowast

S 000 0000lowast

Water parametersCa+ 000 0000Na+ 000 0000

SS (ppm) HCO3

minus 000 0000Clminus 000 0000SAR 000 0000

lowastSignificant at 119901 lt 005

For O viridulus 5939mgL of body loads of heavy metals isrecorded which enable us to conclude that grasshoppers aregood potential metal accumulators

Taking into account that grasshoppers and butterflies areherbivorous insects and crop type is dependent on soil andwater of specific sites soil and water samples were taken foranalysis from same sample sites An analysis of correlationcoefficients (linear 1199032) between metal concentrations andinsects and between soil and water parameters revealed


Table 8 Correlations for each of the insect taxa

Metals Oxya hyla hyla Crocothemis servilia Danaus chrysippusCu Ni Zn Cr Cd Cu Ni Zn Cr Cd Cu Ni Zn Cr Cd

Cu 1 1 03 53 70 minus06 1 minus42 34 24 02Ni minus17 1 1 minus22 minus02 77 1 minus28 19 minus05Zn 09 minus25 1 1 84 minus14 1 57 06Cr minus36 minus01 minus19 1 1 14 1 minus19Cd minus34 minus60 51 45 1 1 1

Table 9 Correlation of soil parameters

Soil parameters pHElectrical

conductivitymsdotmohscm

Organic matter age

Availablephosphorous

(ppm)

Available potash(ppm) Saturation age

pH 1Electricalconductivitymsdotmohscm

120 1

Organic matter age 414 568 1

Availablephosphorous(ppm)

401 571 999lowastlowast 1

Available potash(ppm) 413 570 1000

lowastlowast

1000lowastlowast 1

Saturation age 416 414 856lowastlowast

853lowastlowast

853lowastlowast 1

lowastSignificant at 119901 lt 005lowastlowastSignificant at 119901 lt 001

Table 10 Correlation of water parameters

Water parameters Soluble salts Tss(ppm) Ca++ Mg+ Na+ HCO

3

minus ClminusSodium

absorption ratio(SAR)

Soluble salts Tss (ppm) 1 597 691lowast

719lowast 500 578

Ca++ Mg+ 1 minus116 392 523 minus254Na+ 1 684

lowast

minus024 850lowastlowast

HCO3

minus 1 minus170 296Clminus 1 291Sodium absorption ratio (SAR) 1lowastSignificant at 119901 lt 005lowastlowastSignificant at 119901 lt 001

Table 11 Regression analysis for each of the insect taxa

HMG group Variables Correlation Regression coefficients 119877 square SignificanceDependent Independent 119903 120573

0

1205731

1205732

1205733

1205734

1198772

119901

O hyla hylaCu Ni Zn Cr and Cd 0722 12874 minus62 1684 3370 minus25855 0521 0469Cr Ni Zn Cu and Cd 079 392 0026 0501 minus008 2625 063 030Cd Ni Zn Cr and Cu 0939 172 minus0002 minus0021 0003 0021 0881 0039

C serviliaCu Ni Zn Cr and Cd 0722 12874 minus6214 0684 3370 minus25855 0521 0469Cr Ni Zn Cu and Cd 0797 392 0026 0501 minus0080 26257 0635 0303Cd Ni Zn Cr and Cu 0939 0172 minus0002 minus0021 0003 0021 0881 0039

D chrysippusCu Ni Zn Cr and Cd 0547 75446 minus15492 minus017 1088 5227 0299 0785Cr Ni Zn Cu and Cd 0751 427 0008 0482 0024 minus5365 0564 0404Cd Ni Zn Cr and Cu 0328 0108 0398 0000 0007 0001 minus0019 0968


(B) DragonflyDendrogram using Ward method

Rescaled distance cluster combined

0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E

H I E R A R C H I C A L C L U S T E R A N A L Y S I S

Figure 4 Dendrogram of the cluster analysis (using Wardrsquos Method) applied for metal concentration in dragonfly (C servilia) at nine sites

(C) ButterflyDendrogram using Ward method


0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E


Figure 5 Dendrogram of the cluster analysis (usingWardrsquos Method) applied for metal concentration in butterfly (D chrysippus) at nine sites

significant (119901 lt 005) relationship (Table 10) Our studyfound positive correlation between Cd Cu and Cr for eachof the examined species but not between Zn andNi althoughZn can be replaced by Cd

Urban expansion and further development of industriestanneries in the city would most likely enhance pollutionOne of the major concerns is untreated industrial andmunicipal sewage pollution which poses major threat to theRiver Chenab which is regarded as a pristine aquatic resourceof Punjab province Similarly lives of flora fauna and aboveall humans are at risk due to these untreated and regularlyincreasing industrial and urban wastes

4 Conclusions

The present study highlights the extent of threat to insectand human lives in industrial area of Gujrat as a result ofincreasing metal concentration of Cu Cr Cd Zn and Ni Italso brings forward scope of different insects to be used as toolto study environment quality and conditions The study thusadvocates a need for proper measures to be taken to lessenincreasing environmental pollution (soil air and water) bystrictly implementing pollution control laws and enforcingproper disposal of industrial effluents in industrial zones

Conflict of Interests

The authors declare that there is no conflict of interestsregarding the publication of this paper

References

[1] A Qadir and R N Malik ldquoAssessment of an index of biologicalintegrity (IBI) to quantify the quality of two tributaries of riverChenab Sialkot Pakistanrdquo Hydrobiologia vol 621 no 1 pp127ndash153 2009

[2] Z Atafar A Mesdaghinia J Nouri et al ldquoEffect of fertilizerapplication on soil heavy metal concentrationrdquo EnvironmentalMonitoring and Assessment vol 160 no 1ndash4 pp 83ndash89 2010

[3] C S-L Lee X Li W Shi S C-N Cheung and I ThorntonldquoMetal contamination in urban suburban and country parksoils of Hong Kong a study based on GIS and multivariatestatisticsrdquo Science of the Total Environment vol 356 no 1ndash3 pp45ndash61 2006

[4] A J Davis J D Hollowary H Huijbregts J Krikken A HKirk-Spriggs and S L Sutton ldquoDung beetles as indicators ofchange in the forests of northern Borneordquo Journal of AppliedEcology vol 38 no 3 pp 593ndash616 2001

[5] W Sildanchandra and M Crane ldquoInfluence of sexual dimor-phism in Chironomus riparius Meigen on toxic effects of


cadmiumrdquo Environmental Toxicology and Chemistry vol 19 no9 pp 2309ndash2313 2000

[6] A Zia M A Rafi Z Hussain and M Naeem ldquoOccurrence ofOdonata in northern area of Pakistan with seven new recordsrdquoHalteres vol 1 no 1 pp 48ndash56 2009

[7] A Zia Biosystematics of damselflies (Zygoptera Odonata) ofPakistan [PhD thesis] PMAS-Arid Agriculture UniversityRawalpindi Pakistan 2010

[8] M A Rafi M R Khan A Zia and A Shehzad ldquoDiversity ofOdonata in district Poonch and Sudhnoti of Kashmir Valley-Pakistan with a new record for the countryrdquoHalteres vol 1 no1 pp 28ndash35 2009

[9] A Zia M Naeem and S A Hassan ldquoA list of damselflies(ZygopteraOdonata) recorded fromAzad JammuandKashmir(AJampK)rdquo Pakistan Journal of Science and Industrial Researchvol 51 no 1 pp 329ndash332 2008

[10] T-B Chen Y-M Zheng M Lei et al ldquoAssessment of heavymetal pollution in surface soils of urban parks in BeijingChinardquo Chemosphere vol 60 no 4 pp 542ndash551 2005

[11] C Y Niu Y Jiang C L Lei and C Hu ldquoEffects of cad-mium on housefly influence on growth and development andmetabolism during metamorphosis of houseflyrdquo EntomologiaSinica vol 9 no 1 pp 27ndash33 2002

[12] A Cervera A C Maymo M Sendra R Martınez-Pardoand M D Garcera ldquoCadmium effects on development andreproduction ofOncopeltus fasciatus (Heteroptera Lygaeidae)rdquoJournal of Insect Physiology vol 50 no 8 pp 737ndash749 2004

[13] A Qadir R N Malik and S Z Husain ldquoSpatio-temporalvariations in water quality of Nullah Aik-tributary of the riverChenab Pakistanrdquo Environmental Monitoring and Assessmentvol 140 no 1ndash3 pp 43ndash59 2008

[14] R N Malik and S Z Husain ldquoClassification and ordination ofvegetation communities of the lohibehr reserve forest and itssurrounding areas Rawalpindi Pakistanrdquo Pakistan Journal ofBotany vol 38 no 3 pp 543ndash558 2006

[15] X Li S-I Lee S-C Wong W Shi and IThornton ldquoThe studyof metal contamination in urban soils of Hong Kong using aGIS-based approachrdquo Environmental Pollution vol 129 no 1pp 113ndash124 2004

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Anatomy Research International

PeptidesInternational Journal of


Hindawi Publishing Corporation httpwwwhindawicom

International Journal of

Volume 2014

Zoology


Molecular Biology International

GenomicsInternational Journal of


The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014


BioinformaticsAdvances in

Marine BiologyJournal of



Signal TransductionJournal of


BioMed Research International

Evolutionary BiologyInternational Journal of



Biochemistry Research International

ArchaeaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Genetics Research International


Advances in

Virolog y

Hindawi Publishing Corporationhttpwwwhindawicom

Nucleic AcidsJournal of

Volume 2014

Stem CellsInternational



Enzyme Research



Microbiology


Pakistan

Punjab

Gujrat

Gujrat

32∘29

9984000998400998400N

32∘30

9984000998400998400N

32∘31

9984000998400998400N

32∘32

9984000998400998400N

32∘33

9984000998400998400N

32∘29

9984000998400998400N

32∘30

9984000998400998400N

32∘31

9984000998400998400N

32∘32

9984000998400998400N

32∘33

9984000998400998400N

74∘49984000998400998400E74

∘39984000998400998400E 74

∘59984000998400998400E 74

∘79984000998400998400E74

∘69984000998400998400E

74∘49984000998400998400E74

∘39984000998400998400E 74

∘59984000998400998400E 74

∘79984000998400998400E74

∘69984000998400998400E

End of HalsiNala

Near Chenab River

Kathala ChenabKalra Punwan

Mid of HalsiNala

Kalra Khasa

Start of HalsiNalaSmall Industrial Area

0 25125 100(km)

Sites

7550

Kalra Kalan

N

Chenab_river

Figure 1 Map showing sampling sites (Arc GIS 93)

The reasons for using these insect species as indicatorare follows (1) use of several different taxa of differenthabitat gives more robust results (2) a quantitative indicatorvalue needs to be associated with the bioindicators (3)there is similarity between different landscape features (4)there is comparison of community (5) these taxa can bereliably identified sampled and quantified and (6) morethan one family surely indicate species richness of an order[11] At landscape level strong correlation is found amonggrasshoppers (herbivore) and butterflies (nectivore and her-bivore) Furthermore for bioindication of ecological changewe used aquatic insect dragonfly (Order Odonata) Theyare considered as best ecological indicator in water andriparian systems They give a rapid and sensitive response toaccumulation of heavy metals [12]

Gujrat is an important industrial area of Punjab provinceof Pakistan It is business bay for ceramics fan furnitureand leather industry Qadir et al [13] reported more than1000 cottage-level to large-scale industrial units from thisdistrict In recent past structure ground water and landscapeof Gujrat have been reported to be rapidly degraded dueto industrialization increased urbanization and modernagricultural activities leading to injudicious use of pesticidesand fertilizers [14] Keeping in view environmental andhealth concerns due to increased heavymetal contamination

present study was designed to investigate level of heavymetal contamination in district Gujrat by using insects asbioindicators

2 Materials and Methods

Survey to study heavy metal contamination was carried outduring September 2013 to August 2014 in nine localities(Start of HalsiNala (S1) Kalra Punwan (S2) Mid of HalsiNala(S3) Small Industrial Area (S4) Kalra Kalan (S5) KalraKhasa (S6) Kathala Chenab (S7) Near Chenab River (S8)and End of Nala (S9)) of Tehsil Gujrat (Figure 1) Detailsregarding coordinates and vegetation cover at each samplingsite are shown inTable 1 Siteswere selected at nearest possibledistance to the functioning industrial units Three insectsgroups were chosen to be used as bioindicators It included alibellulid dragonfly (Crocothemis servilia) a nymphalid but-terfly (Danaus chrysippus) and an acridid grasshopper (Oxyahyla hyla)These were collected from rice and wheat crops onquarterly basis for a period of one year Three specimens ofeach group were recorded from each site so the total numberof specimens (sample size) becomes twenty-seven for eachspecies (Table 2) Soil and plant samples were also collectedfrom same sites and stored in sterilized polythene bags untilreaching laboratory Represented specimens of each group



ntype

ofsamplingsites

Sitessele

cted

for

sampling

Site1

Starto

fHalsiN

ala

Site2

Kalra

Punw

anSite3

Mid

ofHalsiN

ala

Site4

SmallInd

ustrial

Area

Site5

Kalra

Kalan

Site6

Kalra

Khasa

Site7

KathalaC

henab

Site8

near

theC

henab

River

Site9

Endof

Nala

Latitud

e32∘

331015840

285810158401015840

N32∘

321015840

536410158401015840

N32∘

331015840

90210158401015840

N32∘

331015840

5870N

32∘

321015840

467310158401015840

N32∘

321015840

449810158401015840

N32∘

311015840

150710158401015840

N32∘

291015840

25771210158401015840

N32∘

311015840

77310158401015840N

Long

itude

74∘

51015840560610158401015840

E74∘

51015840521810158401015840

E74∘

51015840215710158401015840

E74∘

51015840248010158401015840

E74∘

5101584025010158401015840

E74∘

51015840384310158401015840

E74∘

6101584055310158401015840

E74∘

510158403019

9210158401015840

E74∘

51015840398510158401015840

EVe

getatio

nRice

Rice

Rice

Rice

Wheat

Wheat

Wheat

Wheat

Rice


Table2Samplingtim

ealong

with

temperaturehum

idityand

typeso

finsectrecorded

Season

Activ

eseason

Mod

erately

activ

eseason

Mon

th(2013-14)

May

2014

June

2014

July

2014

Aug

2014

Sept

2013

Oct

2013

Nov

2013

Dec

2013

Jan

2013

Feb

2013

Mar

2013

April

2013

Type

ofcrop

s(vegetation)

Rice

Rice

Rice

Rice

Rice

Rice

Rice

Wheat

Wheat

Wheat

Wheat

Wheat

Temperature

(Celsiu

s)33∘

C45∘

C40∘

C32∘

C31∘

C28∘

C25∘

C20∘

C21∘

C25∘

C26∘

C28∘

C

Dew

point

temperature

TD(C

elsiu

s)21∘

C32∘

C28∘

C20∘

C19∘

C17∘

C14∘

C9∘C

10∘

C14∘

C15∘

C17∘

C

Relativeh

umidity

(119891)p

ercent

4926

4902

5084

4903

4880

5123

5053

4922

4955

5053

5077

5123

Typeso

finsects

collected

Butte

rfly

Butte

rfly

grasshop

per

Butte

rfly

grasshop

per

Grassho

pper

Grassho

pper

dragon

flyGrassho

pper

dragon

flyGrassho

pper

dragon

flyBu

tterfly

Butte

rfly

Butte

rfly

Butte

rfly

Butte

rfly

grasshop

pers
















Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


060

040

020

000

Cd

(a)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Cu

(b)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


1500

1000

500

000

Ni

(c)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Zn

(d)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


2000

1500

1000

500

000


HMG

Cr

(e)

















3


(A) Grasshoppers


Label Num0 5 10 15 20 25

S2S6S8S4S7S5S9S3S1

268475931


C A S E





lowastlowast













EC 90 0004lowast

OM 000 0000lowast

pH AP 380 0863AK 000 0000

lowast

S 000 0000lowast


SS (ppm) HCO3












Organic matter age


(ppm)



120 1





lowastlowast

1000lowastlowast 1


853lowastlowast

853lowastlowast 1




3

minus ClminusSodium



719lowast 500 578


lowast


HCO3




0

1205731

1205732

1205733

1205734

1198772

119901







0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E





0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E





4 Conclusions




References

























Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology



ntype

ofsamplingsites

Sitessele

cted

for

sampling

Site1

Starto

fHalsiN

ala

Site2

Kalra

Punw

anSite3

Mid

ofHalsiN

ala

Site4

SmallInd

ustrial

Area

Site5

Kalra

Kalan

Site6

Kalra

Khasa

Site7

KathalaC

henab

Site8

near

theC

henab

River

Site9

Endof

Nala

Latitud

e32∘

331015840

285810158401015840

N32∘

321015840

536410158401015840

N32∘

331015840

90210158401015840

N32∘

331015840

5870N

32∘

321015840

467310158401015840

N32∘

321015840

449810158401015840

N32∘

311015840

150710158401015840

N32∘

291015840

25771210158401015840

N32∘

311015840

77310158401015840N

Long

itude

74∘

51015840560610158401015840

E74∘

51015840521810158401015840

E74∘

51015840215710158401015840

E74∘

51015840248010158401015840

E74∘

5101584025010158401015840

E74∘

51015840384310158401015840

E74∘

6101584055310158401015840

E74∘

510158403019

9210158401015840

E74∘

51015840398510158401015840

EVe

getatio

nRice

Rice

Rice

Rice

Wheat

Wheat

Wheat

Wheat

Rice


Table2Samplingtim

ealong

with

temperaturehum

idityand

typeso

finsectrecorded

Season

Activ

eseason

Mod

erately

activ

eseason

Mon

th(2013-14)

May

2014

June

2014

July

2014

Aug

2014

Sept

2013

Oct

2013

Nov

2013

Dec

2013

Jan

2013

Feb

2013

Mar

2013

April

2013

Type

ofcrop

s(vegetation)

Rice

Rice

Rice

Rice

Rice

Rice

Rice

Wheat

Wheat

Wheat

Wheat

Wheat

Temperature

(Celsiu

s)33∘

C45∘

C40∘

C32∘

C31∘

C28∘

C25∘

C20∘

C21∘

C25∘

C26∘

C28∘

C

Dew

point

temperature

TD(C

elsiu

s)21∘

C32∘

C28∘

C20∘

C19∘

C17∘

C14∘

C9∘C

10∘

C14∘

C15∘

C17∘

C

Relativeh

umidity

(119891)p

ercent

4926

4902

5084

4903

4880

5123

5053

4922

4955

5053

5077

5123

Typeso

finsects

collected

Butte

rfly

Butte

rfly

grasshop

per

Butte

rfly

grasshop

per

Grassho

pper

Grassho

pper

dragon

flyGrassho

pper

dragon

flyGrassho

pper

dragon

flyBu

tterfly

Butte

rfly

Butte

rfly

Butte

rfly

Butte

rfly

grasshop

pers
















Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


060

040

020

000

Cd

(a)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Cu

(b)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


1500

1000

500

000

Ni

(c)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Zn

(d)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


2000

1500

1000

500

000


HMG

Cr

(e)

















3


(A) Grasshoppers


Label Num0 5 10 15 20 25

S2S6S8S4S7S5S9S3S1

268475931


C A S E





lowastlowast













EC 90 0004lowast

OM 000 0000lowast

pH AP 380 0863AK 000 0000

lowast

S 000 0000lowast


SS (ppm) HCO3












Organic matter age


(ppm)



120 1





lowastlowast

1000lowastlowast 1


853lowastlowast

853lowastlowast 1




3

minus ClminusSodium



719lowast 500 578


lowast


HCO3




0

1205731

1205732

1205733

1205734

1198772

119901







0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E





0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E





4 Conclusions




References

























Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology


Table2Samplingtim

ealong

with

temperaturehum

idityand

typeso

finsectrecorded

Season

Activ

eseason

Mod

erately

activ

eseason

Mon

th(2013-14)

May

2014

June

2014

July

2014

Aug

2014

Sept

2013

Oct

2013

Nov

2013

Dec

2013

Jan

2013

Feb

2013

Mar

2013

April

2013

Type

ofcrop

s(vegetation)

Rice

Rice

Rice

Rice

Rice

Rice

Rice

Wheat

Wheat

Wheat

Wheat

Wheat

Temperature

(Celsiu

s)33∘

C45∘

C40∘

C32∘

C31∘

C28∘

C25∘

C20∘

C21∘

C25∘

C26∘

C28∘

C

Dew

point

temperature

TD(C

elsiu

s)21∘

C32∘

C28∘

C20∘

C19∘

C17∘

C14∘

C9∘C

10∘

C14∘

C15∘

C17∘

C

Relativeh

umidity

(119891)p

ercent

4926

4902

5084

4903

4880

5123

5053

4922

4955

5053

5077

5123

Typeso

finsects

collected

Butte

rfly

Butte

rfly

grasshop

per

Butte

rfly

grasshop

per

Grassho

pper

Grassho

pper

dragon

flyGrassho

pper

dragon

flyGrassho

pper

dragon

flyBu

tterfly

Butte

rfly

Butte

rfly

Butte

rfly

Butte

rfly

grasshop

pers
















Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


060

040

020

000

Cd

(a)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Cu

(b)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


1500

1000

500

000

Ni

(c)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Zn

(d)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


2000

1500

1000

500

000


HMG

Cr

(e)

















3


(A) Grasshoppers


Label Num0 5 10 15 20 25

S2S6S8S4S7S5S9S3S1

268475931


C A S E





lowastlowast













EC 90 0004lowast

OM 000 0000lowast

pH AP 380 0863AK 000 0000

lowast

S 000 0000lowast


SS (ppm) HCO3












Organic matter age


(ppm)



120 1





lowastlowast

1000lowastlowast 1


853lowastlowast

853lowastlowast 1




3

minus ClminusSodium



719lowast 500 578


lowast


HCO3




0

1205731

1205732

1205733

1205734

1198772

119901







0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E





0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E





4 Conclusions




References

























Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology
















Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


060

040

020

000

Cd

(a)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Cu

(b)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


1500

1000

500

000

Ni

(c)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


20000

15000

10000

5000

000

Zn

(d)

Mea

n in

sect

s con

cent

ratio

n of

hea

vy m

etal

s


2000

1500

1000

500

000


HMG

Cr

(e)

















3


(A) Grasshoppers


Label Num0 5 10 15 20 25

S2S6S8S4S7S5S9S3S1

268475931


C A S E





lowastlowast













EC 90 0004lowast

OM 000 0000lowast

pH AP 380 0863AK 000 0000

lowast

S 000 0000lowast


SS (ppm) HCO3












Organic matter age


(ppm)



120 1





lowastlowast

1000lowastlowast 1


853lowastlowast

853lowastlowast 1




3

minus ClminusSodium



719lowast 500 578


lowast


HCO3




0

1205731

1205732

1205733

1205734

1198772

119901







0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E





0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E





4 Conclusions




References

























Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology
















3


(A) Grasshoppers


Label Num0 5 10 15 20 25

S2S6S8S4S7S5S9S3S1

268475931


C A S E





lowastlowast













EC 90 0004lowast

OM 000 0000lowast

pH AP 380 0863AK 000 0000

lowast

S 000 0000lowast


SS (ppm) HCO3












Organic matter age


(ppm)



120 1





lowastlowast

1000lowastlowast 1


853lowastlowast

853lowastlowast 1




3

minus ClminusSodium



719lowast 500 578


lowast


HCO3




0

1205731

1205732

1205733

1205734

1198772

119901







0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E





0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E





4 Conclusions




References

























Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology








Organic matter age


(ppm)



120 1





lowastlowast

1000lowastlowast 1


853lowastlowast

853lowastlowast 1




3

minus ClminusSodium



719lowast 500 578


lowast


HCO3




0

1205731

1205732

1205733

1205734

1198772

119901







0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E





0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E





4 Conclusions




References

























Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology




0 5 10 15 20 25

S5S9S3S6S1S7S2S4S8

593617248

Label NumC A S E





0 5 10 15 20 25

S5S8S3S9S2S7S1S6S4

583927164

Label NumC A S E





4 Conclusions




References

























Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology




















Volume 2014

Zoology






















Advances in

Virolog y



Volume 2014




Enzyme Research



Microbiology

research article evaluating insects as bioindicators of...

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