research article ecology of interstitial faunal assemblage ...along the coast of kerala, india...

Research ArticleEcology of Interstitial Faunal Assemblage from the Beachesalong the Coast of Kerala India

Geetha Priyalakshmi1 and N R Menon23

1 Department of Zoology Bharata Mata College Thrikkakara Kochi-682021 Kerala India2 School of Marine Science CUSAT Kochi-682016 Kerala India3 Nansen Environment Research Centre Kochi-682016 Kerala India

Correspondence should be addressed to Geetha Priyalakshmi priyalakshmigyahoocoin

Received 11 August 2013 Accepted 25 November 2013 Published 23 January 2014

Academic Editor Swadhin Behera

Copyright copy 2014 G Priyalakshmi and N R Menon This is an open access article distributed under the Creative CommonsAttribution License which permits unrestricted use distribution and reproduction in any medium provided the original work isproperly cited

A quantitative and qualitative study of interstitial fauna and environmental variables was carried out on five selected sandy beachesof the west coast of India Species of nine interstitial taxa abound the beaches Nematodes harpacticoid copepods turbellariansand polychaetes constituted the bulk of the population The available energy in the beaches ranged from 02245 to 1608 joulesmgand the grain size varied from 093 to 288120593 Organic matter correlated significantly with coarse sand (Pearson correlation 119903 =0651 119875 lt 001) Organic carbon particle size and dissolved oxygen determined the abundance and distribution of interstitialfauna as per multivariate BIOENV analysis ShannonWienerH1015840 diversity index was maximum at Cherai (2027) and minimum atSakthikulangara (1144) beachThe value of nematodecopepod ratio (119873 (2119860)119862 gt 10) indicated at Sakthikulangara beach validatesthe increased sensitivity of harpacticoids to environmental stress

1 Introduction

The coastline of Kerala which extents up to 590 kms is inter-cepted by fishing harbours ports tourist resorts mangrovebeds sandy beaches and so forth [1] Sandy beaches harbourdiverse and abundant assemblage of interstitial organismsand the different taxonomic groups have complex distribu-tion patterns [2] Cyclic sedimentary processes make thebeaches of Kerala fragile A beachmaintained for a particularperiod may not remain there forever The wave climate andthe beach processes along the Kerala coast are found to varyconsiderably in both spatial and temporal frame [3] Erosionadversely affects the density of intertidal interstitial pop-ulations which live in the interstices of beach sedimentsBiodiversity assessment is the key to understand the rela-tionship between biodiversity and ecosystem functioning [4]Hydrodynamics changes the physicochemical sedimentaryenvironment and food availability which are directly relatedto meiofauna spatial distribution patterns [5] Meiofaunaplays a major role in pollution monitoring studies [6 7]

The meiofaunal species are vulnerable to abiotic and hydro-dynamic disturbance [8] Though arguments were tradition-ally put forth against the use of meiofauna as biological indi-cator underlining difficulties in identification the high rateof sampling frequency and the microscopic size of the organ-isms and new technologies and tools such as standard-ized methodologies electronic identification keys molecularapproaches and the creation of new indices currently allowfor and promote the use of meiofauna in ecological studies[9] Though several meiofaunal studies have been conductedon the west coast of India [10ndash16] there is scanty informationon the ecology and taxonomy of interstitial fauna from thesandy beaches of Kerala Further ecological studies of meio-fauna are necessary to understand the trophodynamics ofsandy beaches Although a great deal of uncertainty remainsin our understanding ofmeiofaunal biodiversity ecology andevolutionary biology this area of research remains amongthe most challenging the most neglected and potentially themost enlightening frontiers of discovery in biology [17]

Hindawi Publishing CorporationInternational Journal of OceanographyVolume 2014 Article ID 284979 9 pageshttpdxdoiorg1011552014284979

2 International Journal of Oceanography

2 Materials and Methods

21 Study Area

Study Area Five sandy beaches (Figure 1) such as Cherai(lat10∘091015840N long76∘021015840E St1) Fort Kochi (lat9∘181015840Nlong76∘051015840E St2) Arthungal (lat9∘101015840N long76∘231015840E St3)Sakthikulangara (lat8∘451015840N long76∘381015840E St4) and Veli (lat8∘291015840 N long76∘591015840 E St5) located along the coast of KeralaIndia were identified by site survey to undertake a studyof the psammophilous fauna Cherai and Arthungal beachesare relatively stable and less disturbed Fort Kochi and Velibeaches are affected by industrialization and Sakthikulangarais characterized by natural radioactive pollution of thoriumand presence of large quantities of faecal waste Seasonal col-lections were made for one year (2005-06) Samples were col-lected at two points (100m apart) along a transect from thesubtidal area of each beach by using a galvanized iron coreof 8 cm inner diameter Three undisturbed sediment sampleseach were immediately transferred into bottles 7 MgCl

2

prepared in filtered sea water was added to the sediment sam-ple to anaesthetize the animals The samples were preservedin buffered 4 formalin prepared with filtered seawater 01Rose Bengal [18] was added to the sample for efficient extrac-tion of the fauna Meiofauna was separated by suspension-decantation method [19] with a few modifications [20]

22 Granulometry Sediment samples of approximately 150gms were used from each station for carbon analysis and tex-tural analysis Sediment was subjected to repetitive rinsingand decanting employing distilled water to remove the salin-ity and then dried in an oven under a temperature of 40ndash50∘CThe percentage of organic carbon was estimated with a CHNanalyzer (Elementar Vario III) and the organic carbon valueswere converted to organic matter using a conversion factorof 172 [21] Energy content was obtained using the methodadopted by Barnes [22]

Dry sieving method [23] was followed for the texturalanalysis of the sediment sample since the beach sand con-tained less than 5 silt-clay fraction The equipment for theanalysis consisted of a stacked set of Wentworth grade sieveswith 5 phi (120593) intervals within the range of 62ndash2000 12058380 gm of oven dried salt free sand sample was introducedinto the 2000 120583 sieve at the top of the stack and the stacktransferred to the mechanical shaker and agitated for 15minutes After this the material in each sieve was taken andweighedMaterial (lt62120583m) that had fallen into the pan at thebottom of the sieve stack was also weighed Fraction of thesediment (calculated in percentageweight of the total sample)was transferred into cumulative frequency series and thenplotted as cumulative frequency curve From the resultingsigmoid curve the particle diameter was estimated and inter-preted From the cumulative frequency curve graphic meanand standard deviation were calculated [24] The nature ofsediment was identified based on the verbal classificationmeasure of Folk [24]

23 Hydrography Interstitial water was siphoned out fromthe pit that was made by the core sampler employed to collect

India

Arabian Sea

Kerala

CheraiArthungal

Fort Kochi

VeliSakthikulangara

Bay of Bengal

Longitude (∘E)68 70 72 74 76 78 80 82 84 86 88

6

8

10

12

14

16

18

20

22

Latit

ude (

∘N

)

Figure 1 Sampling locations of the study area

the sediment These samples were analysed for temperature(with a high precisionmercury thermometer) salinity (usinga calibrated salinometer) pH (with Pocket pHTester Eutech)and dissolved oxygen by Winklerrsquos method[25]

24 Ecological Indices

Diversity Indices Species diversity was estimated accordingto Shannon-Wiener 1198671015840(log2) [26]) Margalef rsquos richness (119889)[27] and Pieloursquos evenness (1198691015840) [28] indices The nematode-copepod119873 (2A)C ratio was calculated by dividing the num-ber of nematodes (2119860 trophic group or epigrowth feeders) ina sample by the number of copepods [29]

25 Statistical Analysis The software programmes namelySPSS (Version 110) and PRIMER V6 (Plymouth Routines InMultivariate Ecological Research Version 6) were used forunivariate andmultivariate analysis of data Pearson product-moment correlations were performed to test the relationshipbetween meiofaunal distributions and environmental vari-ables Correlations were considered significant at 119875 lt 001

BEST Analysis The BEST routine available in PRIMER v6combines the BIOENV andBV STEP procedures of PRIMERv5This routine uses all the available environmental variablesto find out the combination that ldquobest explainsrdquo the patternsin the biological data PRIMER v6 for windows was used forthe analysis of community structure

Similarity Indices Multivariate analysis consisted of estimat-ing Bray-Curtis similarity after suitable transformation ofsample abundance data The similarity matrix was subjectedto both clustering (hierarchical agglomerative method usinggroup average linking) and ordination (nonmetric multidi-mensional scaling MDS) using PRIMER v6The significance

International Journal of Oceanography 3

of the clusters formed was tested by the similarity profile(SIMPROF) test

3 Results and Discussion

In marine benthic ecology sediment granulometry alongwith environmental parameters is considered essential todetermine the composition and characterization of benthicorganisms [30]The sediment characteristics and the intersti-tial faunal density are presented in Tables 1 and 2 respectivelyThe nature of sediments varied from very well sorted tomod-erately sortedModerately well sortedmedium sand harboursthe most diverse meiofauna [9] Coarser grains have smallretention capacity than fine ones but on the other hand theyhave larger capacity of circulation [31] Therefore any majorchange in the sedimentary structure results in a change inthe community structure [32] Absence of meiofaunal taxa inpost-monsoon at Fort Kochi beach (Table 2) accompanied bya drastic reduction in the medium sand fraction percentagecorroborates the statement

But a single factor alone cannot be held responsible formeiofaunal reduction The pore volume in poorly sortedsediments is often reduced to 20 The poor sorting of sed-iments at Sakthikulangara beach (Table 1) implies that thetransportation agencies were incapable of separating the sed-iments into different class sizes and differential settling ratesmay be prevalent in the areaThe sandy beaches of Kerala aresubjected to seasonal erosion and accretion Due to variousoceanographic phenomena like upwelling and storm surgesaccompanied by the south west and north east monsoon themorphology beach profile and the physical characteristicsof the beaches alter drastically [3] The variations noticed inthe textural characteristics of the beach sediment are due tothe physical changes that happen to these sandy beachesperiodically

Besides texture organic content of sediment is an impor-tant factor that determines the infaunal distribution since itis a dominant source of food directly for deposit feeders andindirectly for suspension feeders It is generally believed thatsedimentswith coarse particles are deficient in organicmatterwhereas fine grain sediments show organic enrichment [30]However organic matter correlated significantly with coarsesand (Pearson correlation 119903 = 0651 119875 lt 001) at the studiedlocations Unlike the earlier findings that coarse sedimentscontain lesser organic carbon than fine sediments [33] thepresent study revealed that the angularity of sediments couldplay a significant role in the amount of organic carbonadsorbed to the sediments More angular sand particles canharbor more carbon than smooth grains [9 34] Consump-tion of organic matter bound sediments and subsequent gen-eration of faecal pellets will alter the mechanical compositionof sediments The amount of energy available in differentbeaches during the period of study ranged from 02245 to1608 joulesmg (Figure 2) A significant relation was not evi-dent between organic carbon and the numerical abundance ofinterstitial organisms (Table 4) Ansari and Parulekar couldnot observe any consistent pattern between organic carbon

4

6

0

2

8

10

12

14

16

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veli

Ener

gy (j

oule

sm

g)

Pre-monSites

MonsoonPost-mon

Figure 2 Energy content (joulesmg) of the sediment at thedifferent beaches

and benthic biomass [15] It is therefore clear that the qualityof organic matter matters

The hydrographic parameters such as temperature pHsalinity and dissolved oxygen are presented in Table 3 Thefluctuations in temperature of the interstitial water mediumare not very significant in tropical habitats and a temperaturefluctuation of 5∘C is easily endured by the interstitial animals[35] Of the several hydrographic parameters of the mediumthat influence the occurrence and distribution of the intersti-tial forms salinity is by far the most important in a tropicalhabitat An important feature of the study area is the influenceof south west monsoon which affects the hydrographiccondition in a remarkable manner Wide fluctuations insalinity exert great stress upon interstitial organisms Lowsalinity characterized Fort Kochi beach (Table 3)

The beach here is narrow and the lower salinity is due tothe proximity of the channel leading to the backwaters andthe consequent mixing with brackish water [36] The inflowof fresh water greatly affects the interstitial fauna inhabitingthe area Increased salinity is favourable to harpacticoids[37] Low salinity at Fort Kochi beach is marked by theabsence of harpacticoids in the monsoon and post-monsoonseasons of the year (Tables 2 and 3) Great reduction ofmeiofauna abundance has been recorded during periods withreduced salinity after heavy rain [10 38] In tropical beachesalthough the seasons are not markedly delineated periods ofldquogood weatherrdquo and ldquostormsrdquo influence vertical migration ofmeiofauna [39] In the marine biome pH plays only a minorrole for interstitial fauna since the slightly alkaline sea wateris well buffered against pH fluctuation Dissolved oxygen ofthe interstitial water ranged from368 to 805mgLDissolvedoxygen in a sandy beach is dependent on the drainage ofcapillary water and the evaporation of interstitial water in thesurface layers Several reports are available on the correlation


Table 1 Distribution of sand grains in weight percentage (coarse medium and fine sand) and sediment characteristics in the study area

Season Station Sand fraction wt Mean Std Dev Org C Nature of sedimentCoarse Medium Fine 120593

Pre-monsoon

Cherai 7 75 18 168 (310) 047 0065 Well sortedFort Kochi 3 80 17 170 (320) 045 0195 Well sortedArthungal 48 48 4 097 (493) 076 0300 Moderately sortedSakthikulangara 34 20 46 188 (280) 119 285 Poorly sortedVeli 4 84 12 165 (330) 038 0085 Well sorted

Monsoon

Cherai 16 64 20 162 (290) 058 0095 Moderately well sortedFort Kochi 2 50 48 219 (220) 047 058 Well sortedArthungal 20 53 27 167 (320) 075 0485 Moderately sortedSakthikulangara 46 30 24 114 (430) 116 344 Poorly sortedVeli 1 62 37 208 (280) 054 0095 Moderately well sorted

Post-monsoon

Cherai 25 60 15 144 (400) 064 007 Moderately well sortedFort Kochi 1 3 96 288 (140) 019 040 Very well sortedArthungal 16 77 7 142 (365) 045 0175 Well sortedSakthikulangara 46 25 29 140 (440) 122 407 Poorly sortedVeli 12 71 17 162 (330) 049 0065 Well sorted

lowastParticle size in microns

Table 2 Major groups of meiofauna from the study area (density100 cc)

Season Station Nem Poly Oligo Turb Hrpc Gastro Kinor Isop Cnid

Pre-monsoon

Cherai 343 4 9 116 46 7 3 0 0F Kochi 600 348 0 114 950 695 0 0 0Arthungal 238 120 0 6 153 0 0 0 2Sakthi 28 2 0 4 0 0 0 0 0Veli 19 2 0 18 48 2 0 3 0

Monsoon


Post-monsoon


Sakthi Sakthikulangara Nem nematode Poly polychaete Oligo oligochaete Turb turbellarian Hrpc harpacticoid copepod Gastro gastrotrich KinorKinorhyncha Isop isopod Cnid cnidarian

between the meiofaunal abundance and dissolved oxygen[40 41]

Beaches are highly dynamic ecosystems and the study ofmeiofauna in beach ecology is important for the understand-ing of trophodynamic processes [42]The relative abundanceof interstitial organisms (annual mean) in different beaches isillustrated in Figure 3While nematodes were the most abun-dant taxon in Cherai and Sakthikulangara beaches the restof the beaches under study were dominated by harpacticoidcopepods Other groups included turbellarians polychaetesoligochaetes gastrotrichs isopods Kinorhyncha and cnidar-ians It could be seen that the distribution of total interstitial

fauna and the different taxa was by nomeans uniform and theorder of domination of taxa varied with beaches

The Pearson correlation matrix between the various mei-ofauna taxa and the environmental variables is presented inTable 4 Total meiofaunal density is positively correlated withmedium sand at 5 level of significance Harpacticoids andturbellarians correlated at 005 levels with medium sand

Rodrıguez et al [8] found that exposure time desiccationavailability of food sediment granulometry tidal zonationand interstitial water quality are the physical parameters thatregulate the abundance of intertidal meiofauna A multitudeof environmental factors shape the meiofaunal abundance


Table 3 Temperature pH salinity and dissolved oxygen content of the interstitial seawater of the study area

Season Station Temp ∘C pH Sal0 DO mgL

Pre-monsoon

Cherai 26 705 34 575Fort Kochi 29 845 305 374Arthungal 29 785 36 489Sakthikulangara 285 785 325 370Veli 295 740 305 792

Monsoon


Post-monsoon


Mei

ofau

na (

)

OthersCnidIsopKinorGastr

HrpcTurbOligoPolyNem

0

10

20

30

40

50

60

70

80

90

100

Cherai Fort Kochi Arthungal Sakthi-kulangara

Veli

Sampling stations

Figure 3 Relative abundance (annual mean) of meiofauna taxa inthe study area

and distribution of a habitat BEST analysis was done to findthe best possible combination of variables that determinedthe faunal abundance and distribution Biota-Environmentalmatching (BEST) as per the primer analysis (Figures 4 and 5)showed that organic carbon particle size and dissolved oxy-gen were the best combination of variables that determinedthe abundance and distribution of interstitial fauna in thepresent study

Species diversity was estimated according to the Shan-non-Wiener 1198671015840 (log2) diversity Margaleff richness (119889) andPieloursquos evenness (1198691015840) indices (Table 5)

10

0

Freq

uenc

yBEST

minus006

minus004

minus002 0

002

004

006

008

01

012

014

016

018

02

022

024

026

028

03

032

034

036

038

04

042

Rho

Figure 4 Histogram showing the BEST results of the distributionof interstitial fauna based on sediment parameters (Rho = 0202)

Shannon diversity index was maximum (2027) at Cheraiand lowest at Sakthikulangara (1144) Richness was at itspeak in Cherai (0988) and lowest in Sakthikulangara beach(0599) The evenness component (1198691015840) varied in conformitywith 1198671015840 Multivariate analysis consisted of estimating Bray-Curtis similarity after suitable transformation of sampleabundance data The similarity matrix was subjected to bothclustering (hierarchical agglomerative method using groupaverage linking) and ordination (nonmetric multidimen-sional scaling MDS) MDS plot gave a good ordination witha stress value of 008 (Figure 6) Significant differences areobserved in the distribution of taxa between beaches

The nematode-copepod ratio was first used by Raffaelliand Mason [43] as a fast and reliable tool in monitoring thelevel of organic pollution Despite several criticisms on thissimplified relationship [44ndash46] several researchers [47ndash50]still use nematode-copepod ratio in assessing and identifying


Table4Pearsoncorrelationmatrix

ofinterstitialtaxaa

ndhydrograph

icandsedimentp

aram

eterso

fthe

study

area

Meio

Temp

pHSal

DO

CSMS

FSPartS

CH

NNem

Poly

Oligo

Turb

Hrpc

Gastr

Kino

rIsop

Cnid

Others

Meio

1Temp

0025

1pH

0301

0126

1Sal

0177

0132minus0372lowast

1DO

0001

0246minus031minus0012

1CS


0458lowastminus0303

1MS

0376lowast

0172minus0081

0168

0266minus0415lowast

1FSminus0410lowast

0081

0102minus0518lowastlowastminus005minus0315minus0733lowastlowast

1PartS


0549lowastlowastminus0007

0769lowastlowast

0159minus0742lowastlowast

1Cminus0194minus0534lowastlowast

0038

0132minus0308

0651lowastlowastminus0613lowastlowast

0152

0266

1Hminus0184

0492lowastlowast

0017


023

minus021

0161minus0328

1N

0241


0607lowastlowast

0225

0059minus0062

002

0098

004

10233

1Nem


0121

007minus006

80263

0114

minus0315

0353

0076minus0433lowast

0037

1Po

ly0304

000

60378lowast


0168minus0162minus0002minus007minus0085

000

9012

1Oligo

017minus0171

0061minus0034minus013minus0077

0216minus0168minus009minus0233minus0072minus0234

0093

0327

1Tu

rb0525lowastlowastminus0277


0396lowastminus032



0119

1Hrpc

0794lowastlowast

0292

0359


044

1lowastminus0338

0117minus0265

0109

031

0327

0386lowast

0016

0116

1Gastr

0677lowastlowast

0226

0291


0217minus0216


0231

0555lowastlowast

0236minus0021

0433lowast

0480lowastlowast

1Kino

r0633lowastlowast

0079

0085

0153

0291minus0026

0244minus0235


0286

0396lowastminus0101

02

0430lowast

0414lowast

0117

1Isop

064

8lowastlowast

0078

0078

0161

0262minus0013

0262minus0264


022

0288minus0091

016

0113

0643lowastlowast

0049

0781lowastlowast

1Cn

id0513lowastlowast

0071minus0008

0071

0217

0176

0031minus0164


0197


0088

0521lowastlowast

0003

0639lowastlowast

0422lowast

0169

1Others


0261

0285

000

40322minus0339


013

0431lowastminus0151

0148


0333

0254

0124

0531lowastlowast

1lowastCorrelationissig

nificantat0

05level

lowastlowastCorrelationissig

nificantat0

01level

CScoarses

andMSmedium

sand

FSfin

esandPartSparticlesiz

eC

carbon

Hhydrogen

Nn

itrogen

Cnidcnidaria

KinorkinorhynchaIsopiso

podaO

lygooligochaetaGastro

gastro

tricha

PolypolychaetaHrpcharpactic

oidaN

emnem

atod

aTu

rbturbellaria


Table 5 Diversity indices (annual mean) of total interstitial faunaof the five beaches

BeachMargaleffrichness

d

Pieloursquosevenness

J1015840

Shannon Wienerrsquosdiversity index

H1015840 (log 2)Cherai 0988 0695 2027Fort Kochi 0619 0672 1375Arthungal 0786 0681 1751Sakthikulangara 0599 0567 1144Veli 0821 0799 1874

13

0

Freq

uenc

y

minus008

minus006

minus004

minus002

0020

004

006

008

01

012

014

016

018

02

022

024

026

BEST

Rho

Figure 5 Histogram showing the BEST results of the distribution ofinterstitial fauna based on hydrographic parameters (Rho = 0075)

eutrophically enriched or polluted sediments Benthic har-pacticoid copepods are known to be sensitive to sedimentmetal concentration [51] The nematodecopepod ratio [43]with modifications [29 52] was used as an index to monitorpollution of selected beaches Warwick [29] based on hisstudies has suggested that an indication of pollutionmight begiven by ratios around 40 (119873 (2A)C) for fine sediments and10 for sandsThe119873 (2119860)119862 ratio value of around 12 indicatedat Sakthikulangara beach (Figure 7) is indicative of somedisturbance of this beach

Sakthikulangara beach is characterized by natural radi-oactive pollution by thorium (based on secondary data) andfaecal waste disposal Smol et al [54] have reported higherpercentage of nematodes and lower percentage of harpacti-coids within the sewage (TiO

2) dumping area of Dutch coast

Ansari et al [55] also found that copepods are more sensitiveto environmental stress than nematodes in their study ofinterstitial fauna of the shelf region of south east coast ofIndia Though pollution tests have not been conducted andNC value cannot be taken as a sole means of indicator ofpollution various features observed and analysed during thecourse of this study depict a different scenario of Sakthiku-langara beach

The assessment of ecological role and the spatial and tem-poral changes of meiobenthos can be used in environmentalmonitoring programs whose main goal is often to identify

Olygo

Others

Kinor Isop

Turb

HrpcGastro

Nem

Poly

Cnid 2D Stress 008

2040

6080

Similarity

Transform square rootResemblance S17 Bray Curtis similarity

Figure 6 Nonmetric multidimensional scaling (MDS) ordina-tion plot (stress = 008) of interstitial taxa (Cnid cnidariaKinor kinorhyncha Isop isopoda Olygo oligochaeta Gastro gas-trotricha Poly polychaeta Hrpc harpacticoida Nem nematodaTurb turbellaria)

0

50

100

150

200

250

300

350

0

2

4

6

8

10

12

14

Nem

atod

e co

pepo

d ra

tio

NC ratioCopepods

Cop

epod

s100

ccm

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veil

Figure 7 Nematode to copepod ratio (bars) and the mean numberof harpacticoid copepods (line) over the range of beaches sampledThe three divisions of the graph were proposed by Lee et al (2001)[53]

patterns in community structure and to relate them tomeasured environmental variables including pollutants [42]Cherai beach supported maximum diversity and abundanceof interstitial taxa Further analysis with the help of availableprimary data would be carried out to explain the trophody-namics and ecology of the nematodes and harpacticoids ofCherai and Sakthikulangara beaches


4 Conclusion

Nine interstitial taxa dominated by nematodes and harpacti-coids abound the five ecologically vibrant beaches of KeralaThe organic matter in the beaches ranged from 001 to 0745and the grain size varied from 093 to 288120593 Organic mattercorrelated significantly with coarse sand (Pearson correlation119903 = 0651 119875 lt 001) The angularity of sediments plays asignificant role in the amount of organic carbon adsorbed tothe sediments Total meiofaunal density correlated positivelywith medium sand (119903 = 038 119875 lt 005) Organic carbonparticle size and dissolved oxygen determined the abun-dance and distribution of interstitial fauna as permultivariateBIOENV analysis Diversity index (Shannon Wiener 1198671015840)was maximum at Cherai (2027) indicating the stability ofenvironmental parameters and minimum at Sakthikulangara(144) characterized by regular physical changes The valueof nematodecopepod ratio (119873 (2119860)119862 gt 10) obtainedfor Sakthikulangara beach indicate disturbed nature of thisbeach Nonmetric multidimensional scaling MDS (stress =008) and cluster analysis (similarity profile SIMPROFtest) revealed significant differences in special distributionpatterns of various interstitial taxa

Conflict of Interests

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

Acknowledgments

Priyalakshmi Geetha is thankful to the authorities of BharataMata CollegeThrikkakara Kochi for the assistance and helpand N R Menon the EU Incolab Grant no 295092 for thework They are also thankful for the constructive commentsand suggestions of two anonymous referees on an earlier draftof the paper

References

[1] P Kaladharan D Prema A Nandakumar and K K ValsalaldquoOccurrence of tarball andwastematerials on the beaches alongKerala coast in Indiardquo Journal of the Marine Biological Associa-tion of India vol 46 no 1 pp 93ndash97 2004

[2] F Elaine Albuquerque A P B Pinto A Perez and V G VelosoldquoSpatial and temporal changes in interstitial meiofauna on asandy ocean beach of South Americardquo Brazilian Journal ofOceanography vol 55 no 2 2007

[3] M Baba ldquoWave characteristics and beach processes of thesouth-west coast of Indiamdasha summaryrdquo in Ocean Waves andBeach Processes M Baba and N P Kurien Eds pp 225ndash2381988

[4] S Creer V G Fonseca D L Porazinska et al ldquoUltrasequencingof the meiofaunal biosphere practice pitfalls and promisesrdquoMolecular Ecology vol 19 supplement 1 pp 4ndash20 2010

[5] T K de Oliveira Pinto and P J Parreira Dos Santos ldquoMeiofaunacommunity structure variability in a Brazilian tropical sandybeachrdquo Atlantica Rio Grande vol 28 no 2 pp 117ndash127 2006

[6] H-U Dahms S Chullasorn N V Schizas P Kangtia WAnansatitporn andW-X Yang ldquoNaupliar development among

the tisbidae (Copepoda Harpacticidae) with a phylogeneticanalysis and naupliar description of Tisbe thailandensis fromThailandrdquo Zoological Studies vol 48 no 6 pp 780ndash796 2009

[7] T Yamanaka D Raffaelli and P C LWhite ldquoPhysical determi-nants of intertidal communities on dissipative beaches implica-tions of sea-level riserdquo Estuarine Coastal and Shelf Science vol88 no 2 pp 267ndash278 2010

[8] J G Rodrıguez M Lastra and J Lopez ldquoMeiofauna distri-bution along a gradient of sandy beaches in northern SpainrdquoEstuarine Coastal and Shelf Science vol 58 pp 63ndash69 2003

[9] O Giere ldquoSynecological perspectives in meiobenthologyrdquo inMeiobenthology the Microscopic Motile Fauna of Aquatic Sed-iments vol 2nd pp 406ndash416 Springer 2009

[10] A G Govindankutty and N B Nair ldquoPreliminary observationson the interstitial fauna of the south-west coast of IndiardquoHydro-biologia vol 28 no 1 pp 101ndash112 1966

[11] K C Rajan Studies on the interstitial fauna of the southwest coastof India [PhD thesis] University of Kerala 1972

[12] R Damodaran ldquoStudies on the benthos of themud banks of theKerala coastrdquo Bulletin of the Department of Marine Sciences vol6 pp 1ndash126 1973

[13] P K Abdul Aziz and N B Nair ldquoMeiofauna of the EdavanamdashNadayara Paravur backwater system south west coast of IndiardquoMahasagar Bulletin of the National Institute of Oceanographyvol 16 no 1 pp 55ndash65 1983

[14] B S Ingole Z A Ansari and A H Parulekar ldquoBenthic faunaaround Mauritius Island southwest Indian Oceanrdquo IndianJournal of Marine Sciences vol 21 no 4 pp 268ndash273 1992

[15] Z A Ansari and A H Parulekar ldquoDistribution abundance andecology of the meiofauna in a tropical estuary along the westcoast of Indiardquo Hydrobiologia vol 262 no 2 pp 115ndash126 1993

[16] S Sajan T V Joydas and R Damodaran ldquoMeiofauna of thewestern continental shelf of India Arabian Seardquo EstuarineCoastal and Shelf Science vol 86 no 4 pp 665ndash674 2010

[17] R J Rundell and B S Leander ldquoMasters of miniaturizationconvergent evolution among interstitial eukaryotesrdquo BioEssaysvol 32 no 5 pp 430ndash437 2010

[18] O Pfannkuche and H Thiel ldquoSample processingrdquo in Introduc-tion to the Study of Meiofauna R P Higgins and H Thiel Edspp 134ndash145 Smithsonian Institution Washington DC USA1988

[19] WWieser ldquoBenthic studies in buzzards bay IIThemeiofaunardquoLimnology and Oceanography vol 5 pp 121ndash137 1960

[20] C Neira and M Rackemann ldquoBlack spots produced by buriedmacroalgae in intertidal sandy sediments of the Wadden seaeffects on the meiobenthosrdquo Journal of Sea Research vol 36 no3-4 pp 153ndash170 1996

[21] J D H Wiseman and H E Bennette ldquoDistribution of organicmatter and nitrogen in the sediments from the Arabian SeardquoJohn Murray Expedition vol 3 1960

[22] H Barnes Apparatus and Methods in Oceanography Part IGeorge Allen amp Unwin London UK 1959

[23] J B Buchanan ldquoSediment Analysisrdquo in Methods for the Studyof Marine Benthos N A Holme and A D McIntyre Eds vol16 of IBP Handbook pp 41ndash65 Blackwell Oxford 2nd edition1984

[24] R L Folk Petrology of Sedimentary Rocks Hemphil AustinTexas USA 1974

[25] J D H Strickland and T R Parsons ldquoA practical handbook ofSeawater analysisrdquo in Bulletin of the Fisheries Research Board ofCanada vol 167 pp 1ndash310 2nd edition 1972


[26] C E Shannon andWWienerTheMathematicalTheory of Com-munication Usbana University of Illinoi Press 1949

[27] E H Simpson ldquoMeasurement of diversityrdquoNature vol 163 no4148 p 688 1949

[28] E C Pielou Ed An Introduction to Mathematical EcologyWiley-Interscience New York NY USA 1969

[29] R M Warwick ldquoThe nematodecopepod ratio and its use inpollution ecologyrdquoMarine Pollution Bulletin vol 12 no 10 pp329ndash333 1981

[30] T Ganesh and A V Raman ldquoMacrobenthic community struc-ture of the northeast Indian shelf Bay of BengalrdquoMarine Ecol-ogy Progress Series vol 341 pp 59ndash73 2007

[31] J W NybakkenMarine Biology an Ecological Approach Addi-soon-Wesley Boston Mass USA 1996

[32] P J Somerfield H L Rees and R M Warwick ldquoInterrelation-ships in community structure between shallow-water marinemeiofauna and macrofauna in relation to dredgings disposalrdquoMarine Ecology Progress Series vol 127 no 1ndash3 pp 103ndash1121995

[33] P S Meadows and J G Anderson ldquoMicro-organisms attachedtomarine and freshwater sand grainsrdquoNature vol 212 no 5066pp 1059ndash1060 1966

[34] D McIntyre and D J Murison ldquoThe meiofauna of a flatfishnursery groundrdquo Journal of the Marine Biological Association ofthe United Kingdom vol 53 pp 93ndash118 1973

[35] B O Jansson and Quantitative a ldquoExperimental Studies of theInterstitial Fauna in Four Swedish Beachesrdquo Ophelia vol 5 pp1ndash72 1968

[36] A Trevallion A D Ansell P Sivadas and B Narayanan ldquoApreliminary account of two sandy beaches in SouthWest IndiardquoMarine Biology vol 6 no 3 pp 268ndash279 1970

[37] B S Ingole and A H Parulekar ldquoRole of salinity in structuringthe intertidal meiofauna of a tropical estuarine beach fieldevidencerdquo Indian Journal of Marine Sciences vol 27 no 3-4 pp356ndash361 1998

[38] P N Ganapati and G C Rao ldquoEcology of the interstitial faunainhabiting the sandy beaches of Waltair coastrdquo Journal of theMarine Biological Association of India vol 4 no 1 pp 44ndash571962

[39] VMA P Silva PAGrohmann andC S RNogueira ldquoStudiesof meiofauna of Rio de Janeiro BrazilrdquoCoastal Zone vol 91 no3 pp 2011ndash2022 1991

[40] C A I Lizhe F U Sujing Y Jie and Z X Ping ldquoDistribution ofmeiofaunal abundance in relation to environmental factors inBeibu Gulf South Chinardquo Acta Oceanologica Sinica vol 31 pp92ndash103 2012

[41] G Mantha M S N Moorthy K Altaff et al ldquoSeasonal shifts ofmeiofauna community structures on sandy beaches along theChennai coast Indiardquo Crustaceana vol 85 no 1 pp 27ndash532012

[42] M Moreno T J Ferrero V Granelli V Marin G Albertelliand M Fabiano ldquoAcross shore variability and trophodynamicfeatures of meiofauna in amicrotidal beach of the NWMediter-raneanrdquo Estuarine Coastal and Shelf Science vol 66 no 3-4 pp357ndash367 2006

[43] D G Raffaelli and C F Mason ldquoPollution monitoring withmeiofauna using the ratio of nematodes to copepodsrdquo MarinePollution Bulletin vol 12 no 5 pp 158ndash163 1981

[44] BCCoull G R FHicks and J B JWells ldquoNematodecopepodratios for monitoring pollution a rebuttalrdquo Marine PollutionBulletin vol 12 no 11 pp 378ndash381 1981

[45] P J D Lambshead ldquoThe nematodecopepod ratio Some anom-alous results from the Firth of ClyderdquoMarine Pollution Bulletinvol 15 no 7 pp 256ndash259 1984

[46] R Danovaro M Fabiano and M Vincx ldquoMeiofauna responseto the Agip Abruzzo oil spill in subtidal sediments of theLigurian SeardquoMarine Pollution Bulletin vol 30 no 2 pp 133ndash145 1995

[47] S Amjad and J S Gray ldquoUse of the nematode-copepod ratio asan index of organic pollutionrdquoMarine Pollution Bulletin vol 14no 5 pp 178ndash181 1983

[48] T F Sutherland C D Levings S A Petersen P Poon and BPiercey ldquoThe use of meiofauna as an indicator of benthicorganic enrichment associated with salmonid aquaculturerdquoMarine Pollution Bulletin vol 54 no 8 pp 1249ndash1261 2007

[49] M Moreno L Vezzulli V Marin P Laconi G Albertelli andM Fabiano ldquoThe use of meiofauna diversity as an indicator ofpollution in harboursrdquo ICES Journal of Marine Science vol 65no 8 pp 1428ndash1435 2008

[50] P Veiga C Besteiro and M Rubal ldquoMeiofauna communitiesin exposed sandy beaches on the Galician coast (NWSpain) sixmonths after the Prestige oil spill the role of polycyclic aromatichydrocarbons (PAHs)rdquo Scientia Marina vol 74 no 2 pp 385ndash394 2010


[52] G M Shiells and K J Anderson ldquoPollution monitoring usingthe nematodecopepod ratio A practical applicationrdquo MarinePollution Bulletin vol 16 no 2 pp 62ndash68 1985

[53] M R Lee J A Correa and J C Castilla ldquoAn assessment of thepotential use of the Nematode to copepod ratio in the moni-toring of metal pollutionmdashthe chanaral caserdquoMarine PollutionBulletin vol 42 no 8 pp 696ndash701 2001

[54] N Smol R Huys and M Vincx ldquoA four year analyses of themeiofauna community of a dumping site for TiO

2waste off the

Dutch coastrdquo Chemistry and Ecology vol 5 pp 197ndash215 1991[55] K G M T Ansari P S Lyla S Ajmal Khan S Manokaran and

S Raja ldquoCommunity structure of harpacticoid copepods fromthe south east continental shelf of IndiardquoProceedings of the Inter-national Academy of Ecology and Environmental Sciences vol 3no 2 pp 87ndash100 2013

Submit your manuscripts athttpwwwhindawicom

Hindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ClimatologyJournal of

EcologyInternational Journal of


EarthquakesJournal of


Hindawi Publishing Corporationhttpwwwhindawicom

Applied ampEnvironmentalSoil Science

Volume 2014

Mining


Journal of

Hindawi Publishing Corporation httpwwwhindawicom Volume 2014

International Journal of

Geophysics

OceanographyInternational Journal of


Journal of Computational Environmental SciencesHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal ofPetroleum Engineering


GeochemistryHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Journal of

Atmospheric SciencesInternational Journal of


OceanographyHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

Advances in


MineralogyInternational Journal of


MeteorologyAdvances in

The Scientific World JournalHindawi Publishing Corporation httpwwwhindawicom Volume 2014

Paleontology JournalHindawi Publishing Corporationhttpwwwhindawicom Volume 2014

ScientificaHindawi Publishing Corporationhttpwwwhindawicom Volume 2014


Geological ResearchJournal of


Geology Advances in


2 Materials and Methods

21 Study Area

Study Area Five sandy beaches (Figure 1) such as Cherai(lat10∘091015840N long76∘021015840E St1) Fort Kochi (lat9∘181015840Nlong76∘051015840E St2) Arthungal (lat9∘101015840N long76∘231015840E St3)Sakthikulangara (lat8∘451015840N long76∘381015840E St4) and Veli (lat8∘291015840 N long76∘591015840 E St5) located along the coast of KeralaIndia were identified by site survey to undertake a studyof the psammophilous fauna Cherai and Arthungal beachesare relatively stable and less disturbed Fort Kochi and Velibeaches are affected by industrialization and Sakthikulangarais characterized by natural radioactive pollution of thoriumand presence of large quantities of faecal waste Seasonal col-lections were made for one year (2005-06) Samples were col-lected at two points (100m apart) along a transect from thesubtidal area of each beach by using a galvanized iron coreof 8 cm inner diameter Three undisturbed sediment sampleseach were immediately transferred into bottles 7 MgCl

2

prepared in filtered sea water was added to the sediment sam-ple to anaesthetize the animals The samples were preservedin buffered 4 formalin prepared with filtered seawater 01Rose Bengal [18] was added to the sample for efficient extrac-tion of the fauna Meiofauna was separated by suspension-decantation method [19] with a few modifications [20]

22 Granulometry Sediment samples of approximately 150gms were used from each station for carbon analysis and tex-tural analysis Sediment was subjected to repetitive rinsingand decanting employing distilled water to remove the salin-ity and then dried in an oven under a temperature of 40ndash50∘CThe percentage of organic carbon was estimated with a CHNanalyzer (Elementar Vario III) and the organic carbon valueswere converted to organic matter using a conversion factorof 172 [21] Energy content was obtained using the methodadopted by Barnes [22]

Dry sieving method [23] was followed for the texturalanalysis of the sediment sample since the beach sand con-tained less than 5 silt-clay fraction The equipment for theanalysis consisted of a stacked set of Wentworth grade sieveswith 5 phi (120593) intervals within the range of 62ndash2000 12058380 gm of oven dried salt free sand sample was introducedinto the 2000 120583 sieve at the top of the stack and the stacktransferred to the mechanical shaker and agitated for 15minutes After this the material in each sieve was taken andweighedMaterial (lt62120583m) that had fallen into the pan at thebottom of the sieve stack was also weighed Fraction of thesediment (calculated in percentageweight of the total sample)was transferred into cumulative frequency series and thenplotted as cumulative frequency curve From the resultingsigmoid curve the particle diameter was estimated and inter-preted From the cumulative frequency curve graphic meanand standard deviation were calculated [24] The nature ofsediment was identified based on the verbal classificationmeasure of Folk [24]

23 Hydrography Interstitial water was siphoned out fromthe pit that was made by the core sampler employed to collect

India

Arabian Sea

Kerala

CheraiArthungal

Fort Kochi

VeliSakthikulangara

Bay of Bengal

Longitude (∘E)68 70 72 74 76 78 80 82 84 86 88

6

8

10

12

14

16

18

20

22

Latit

ude (

∘N

)

Figure 1 Sampling locations of the study area

the sediment These samples were analysed for temperature(with a high precisionmercury thermometer) salinity (usinga calibrated salinometer) pH (with Pocket pHTester Eutech)and dissolved oxygen by Winklerrsquos method[25]

24 Ecological Indices

Diversity Indices Species diversity was estimated accordingto Shannon-Wiener 1198671015840(log2) [26]) Margalef rsquos richness (119889)[27] and Pieloursquos evenness (1198691015840) [28] indices The nematode-copepod119873 (2A)C ratio was calculated by dividing the num-ber of nematodes (2119860 trophic group or epigrowth feeders) ina sample by the number of copepods [29]

25 Statistical Analysis The software programmes namelySPSS (Version 110) and PRIMER V6 (Plymouth Routines InMultivariate Ecological Research Version 6) were used forunivariate andmultivariate analysis of data Pearson product-moment correlations were performed to test the relationshipbetween meiofaunal distributions and environmental vari-ables Correlations were considered significant at 119875 lt 001

BEST Analysis The BEST routine available in PRIMER v6combines the BIOENV andBV STEP procedures of PRIMERv5This routine uses all the available environmental variablesto find out the combination that ldquobest explainsrdquo the patternsin the biological data PRIMER v6 for windows was used forthe analysis of community structure

Similarity Indices Multivariate analysis consisted of estimat-ing Bray-Curtis similarity after suitable transformation ofsample abundance data The similarity matrix was subjectedto both clustering (hierarchical agglomerative method usinggroup average linking) and ordination (nonmetric multidi-mensional scaling MDS) using PRIMER v6The significance







4

6

0

2

8

10

12

14

16

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veli

Ener

gy (j

oule

sm

g)

Pre-monSites

MonsoonPost-mon








Pre-monsoon


Monsoon


Post-monsoon





Pre-monsoon


Monsoon


Post-monsoon











Pre-monsoon


Monsoon


Post-monsoon


Mei

ofau

na (

)



0

10

20

30

40

50

60

70

80

90

100


Veli

Sampling stations




10

0

Freq

uenc

yBEST

minus006

minus004

minus002 0

002

004

006

008

01

012

014

016

018

02

022

024

026

028

03

032

034

036

038

04

042

Rho






ofinterstitialtaxaa

ndhydrograph

icandsedimentp

aram

eterso

fthe

study

area

Meio

Temp

pHSal

DO

CSMS

FSPartS

CH

NNem

Poly

Oligo

Turb

Hrpc

Gastr

Kino

rIsop

Cnid

Others

Meio

1Temp

0025

1pH

0301

0126

1Sal

0177

0132minus0372lowast

1DO

0001


1CS


0458lowastminus0303

1MS

0376lowast

0172minus0081

0168

0266minus0415lowast

1FSminus0410lowast

0081


1PartS



0769lowastlowast



0038

0132minus0308


0152

0266

1Hminus0184

0492lowastlowast

0017


023

minus021

0161minus0328

1N

0241


0607lowastlowast

0225

0059minus0062

002

0098

004

10233

1Nem


0121

007minus006

80263

0114

minus0315

0353

0076minus0433lowast

0037

1Po

ly0304

000

60378lowast



000

9012

1Oligo

017minus0171



0093

0327

1Tu



0396lowastminus032



0119

1Hrpc

0794lowastlowast

0292

0359


044

1lowastminus0338

0117minus0265

0109

031

0327

0386lowast

0016

0116

1Gastr

0677lowastlowast

0226

0291


0217minus0216


0231

0555lowastlowast

0236minus0021

0433lowast

0480lowastlowast

1Kino

r0633lowastlowast

0079

0085

0153

0291minus0026

0244minus0235


0286

0396lowastminus0101

02

0430lowast

0414lowast

0117

1Isop

064

8lowastlowast

0078

0078

0161

0262minus0013

0262minus0264


022

0288minus0091

016

0113

0643lowastlowast

0049

0781lowastlowast

1Cn

id0513lowastlowast

0071minus0008

0071

0217

0176

0031minus0164


0197


0088

0521lowastlowast

0003

0639lowastlowast

0422lowast

0169

1Others


0261

0285

000

40322minus0339


013

0431lowastminus0151

0148


0333

0254

0124

0531lowastlowast


nificantat0

05level


nificantat0

01level

CScoarses

andMSmedium

sand

FSfin


eC

carbon

Hhydrogen

Nn

itrogen

Cnidcnidaria


podaO


gastro

tricha


oidaN

emnem

atod

aTu

rbturbellaria




d


J1015840



13

0

Freq

uenc

y

minus008

minus006

minus004

minus002

0020

004

006

008

01

012

014

016

018

02

022

024

026

BEST

Rho







Olygo

Others

Kinor Isop

Turb

HrpcGastro

Nem

Poly

Cnid 2D Stress 008

2040

6080

Similarity



0

50

100

150

200

250

300

350

0

2

4

6

8

10

12

14

Nem

atod

e co

pepo

d ra

tio

NC ratioCopepods

Cop

epod

s100

ccm

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veil




4 Conclusion




Acknowledgments


References

























































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in







4

6

0

2

8

10

12

14

16

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veli

Ener

gy (j

oule

sm

g)

Pre-monSites

MonsoonPost-mon








Pre-monsoon


Monsoon


Post-monsoon





Pre-monsoon


Monsoon


Post-monsoon











Pre-monsoon


Monsoon


Post-monsoon


Mei

ofau

na (

)



0

10

20

30

40

50

60

70

80

90

100


Veli

Sampling stations




10

0

Freq

uenc

yBEST

minus006

minus004

minus002 0

002

004

006

008

01

012

014

016

018

02

022

024

026

028

03

032

034

036

038

04

042

Rho






ofinterstitialtaxaa

ndhydrograph

icandsedimentp

aram

eterso

fthe

study

area

Meio

Temp

pHSal

DO

CSMS

FSPartS

CH

NNem

Poly

Oligo

Turb

Hrpc

Gastr

Kino

rIsop

Cnid

Others

Meio

1Temp

0025

1pH

0301

0126

1Sal

0177

0132minus0372lowast

1DO

0001


1CS


0458lowastminus0303

1MS

0376lowast

0172minus0081

0168

0266minus0415lowast

1FSminus0410lowast

0081


1PartS



0769lowastlowast



0038

0132minus0308


0152

0266

1Hminus0184

0492lowastlowast

0017


023

minus021

0161minus0328

1N

0241


0607lowastlowast

0225

0059minus0062

002

0098

004

10233

1Nem


0121

007minus006

80263

0114

minus0315

0353

0076minus0433lowast

0037

1Po

ly0304

000

60378lowast



000

9012

1Oligo

017minus0171



0093

0327

1Tu



0396lowastminus032



0119

1Hrpc

0794lowastlowast

0292

0359


044

1lowastminus0338

0117minus0265

0109

031

0327

0386lowast

0016

0116

1Gastr

0677lowastlowast

0226

0291


0217minus0216


0231

0555lowastlowast

0236minus0021

0433lowast

0480lowastlowast

1Kino

r0633lowastlowast

0079

0085

0153

0291minus0026

0244minus0235


0286

0396lowastminus0101

02

0430lowast

0414lowast

0117

1Isop

064

8lowastlowast

0078

0078

0161

0262minus0013

0262minus0264


022

0288minus0091

016

0113

0643lowastlowast

0049

0781lowastlowast

1Cn

id0513lowastlowast

0071minus0008

0071

0217

0176

0031minus0164


0197


0088

0521lowastlowast

0003

0639lowastlowast

0422lowast

0169

1Others


0261

0285

000

40322minus0339


013

0431lowastminus0151

0148


0333

0254

0124

0531lowastlowast


nificantat0

05level


nificantat0

01level

CScoarses

andMSmedium

sand

FSfin


eC

carbon

Hhydrogen

Nn

itrogen

Cnidcnidaria


podaO


gastro

tricha


oidaN

emnem

atod

aTu

rbturbellaria




d


J1015840



13

0

Freq

uenc

y

minus008

minus006

minus004

minus002

0020

004

006

008

01

012

014

016

018

02

022

024

026

BEST

Rho







Olygo

Others

Kinor Isop

Turb

HrpcGastro

Nem

Poly

Cnid 2D Stress 008

2040

6080

Similarity



0

50

100

150

200

250

300

350

0

2

4

6

8

10

12

14

Nem

atod

e co

pepo

d ra

tio

NC ratioCopepods

Cop

epod

s100

ccm

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veil




4 Conclusion




Acknowledgments


References

























































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in




Pre-monsoon


Monsoon


Post-monsoon





Pre-monsoon


Monsoon


Post-monsoon











Pre-monsoon


Monsoon


Post-monsoon


Mei

ofau

na (

)



0

10

20

30

40

50

60

70

80

90

100


Veli

Sampling stations




10

0

Freq

uenc

yBEST

minus006

minus004

minus002 0

002

004

006

008

01

012

014

016

018

02

022

024

026

028

03

032

034

036

038

04

042

Rho






ofinterstitialtaxaa

ndhydrograph

icandsedimentp

aram

eterso

fthe

study

area

Meio

Temp

pHSal

DO

CSMS

FSPartS

CH

NNem

Poly

Oligo

Turb

Hrpc

Gastr

Kino

rIsop

Cnid

Others

Meio

1Temp

0025

1pH

0301

0126

1Sal

0177

0132minus0372lowast

1DO

0001


1CS


0458lowastminus0303

1MS

0376lowast

0172minus0081

0168

0266minus0415lowast

1FSminus0410lowast

0081


1PartS



0769lowastlowast



0038

0132minus0308


0152

0266

1Hminus0184

0492lowastlowast

0017


023

minus021

0161minus0328

1N

0241


0607lowastlowast

0225

0059minus0062

002

0098

004

10233

1Nem


0121

007minus006

80263

0114

minus0315

0353

0076minus0433lowast

0037

1Po

ly0304

000

60378lowast



000

9012

1Oligo

017minus0171



0093

0327

1Tu



0396lowastminus032



0119

1Hrpc

0794lowastlowast

0292

0359


044

1lowastminus0338

0117minus0265

0109

031

0327

0386lowast

0016

0116

1Gastr

0677lowastlowast

0226

0291


0217minus0216


0231

0555lowastlowast

0236minus0021

0433lowast

0480lowastlowast

1Kino

r0633lowastlowast

0079

0085

0153

0291minus0026

0244minus0235


0286

0396lowastminus0101

02

0430lowast

0414lowast

0117

1Isop

064

8lowastlowast

0078

0078

0161

0262minus0013

0262minus0264


022

0288minus0091

016

0113

0643lowastlowast

0049

0781lowastlowast

1Cn

id0513lowastlowast

0071minus0008

0071

0217

0176

0031minus0164


0197


0088

0521lowastlowast

0003

0639lowastlowast

0422lowast

0169

1Others


0261

0285

000

40322minus0339


013

0431lowastminus0151

0148


0333

0254

0124

0531lowastlowast


nificantat0

05level


nificantat0

01level

CScoarses

andMSmedium

sand

FSfin


eC

carbon

Hhydrogen

Nn

itrogen

Cnidcnidaria


podaO


gastro

tricha


oidaN

emnem

atod

aTu

rbturbellaria




d


J1015840



13

0

Freq

uenc

y

minus008

minus006

minus004

minus002

0020

004

006

008

01

012

014

016

018

02

022

024

026

BEST

Rho







Olygo

Others

Kinor Isop

Turb

HrpcGastro

Nem

Poly

Cnid 2D Stress 008

2040

6080

Similarity



0

50

100

150

200

250

300

350

0

2

4

6

8

10

12

14

Nem

atod

e co

pepo

d ra

tio

NC ratioCopepods

Cop

epod

s100

ccm

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veil




4 Conclusion




Acknowledgments


References

























































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in




Pre-monsoon


Monsoon


Post-monsoon


Mei

ofau

na (

)



0

10

20

30

40

50

60

70

80

90

100


Veli

Sampling stations




10

0

Freq

uenc

yBEST

minus006

minus004

minus002 0

002

004

006

008

01

012

014

016

018

02

022

024

026

028

03

032

034

036

038

04

042

Rho






ofinterstitialtaxaa

ndhydrograph

icandsedimentp

aram

eterso

fthe

study

area

Meio

Temp

pHSal

DO

CSMS

FSPartS

CH

NNem

Poly

Oligo

Turb

Hrpc

Gastr

Kino

rIsop

Cnid

Others

Meio

1Temp

0025

1pH

0301

0126

1Sal

0177

0132minus0372lowast

1DO

0001


1CS


0458lowastminus0303

1MS

0376lowast

0172minus0081

0168

0266minus0415lowast

1FSminus0410lowast

0081


1PartS



0769lowastlowast



0038

0132minus0308


0152

0266

1Hminus0184

0492lowastlowast

0017


023

minus021

0161minus0328

1N

0241


0607lowastlowast

0225

0059minus0062

002

0098

004

10233

1Nem


0121

007minus006

80263

0114

minus0315

0353

0076minus0433lowast

0037

1Po

ly0304

000

60378lowast



000

9012

1Oligo

017minus0171



0093

0327

1Tu



0396lowastminus032



0119

1Hrpc

0794lowastlowast

0292

0359


044

1lowastminus0338

0117minus0265

0109

031

0327

0386lowast

0016

0116

1Gastr

0677lowastlowast

0226

0291


0217minus0216


0231

0555lowastlowast

0236minus0021

0433lowast

0480lowastlowast

1Kino

r0633lowastlowast

0079

0085

0153

0291minus0026

0244minus0235


0286

0396lowastminus0101

02

0430lowast

0414lowast

0117

1Isop

064

8lowastlowast

0078

0078

0161

0262minus0013

0262minus0264


022

0288minus0091

016

0113

0643lowastlowast

0049

0781lowastlowast

1Cn

id0513lowastlowast

0071minus0008

0071

0217

0176

0031minus0164


0197


0088

0521lowastlowast

0003

0639lowastlowast

0422lowast

0169

1Others


0261

0285

000

40322minus0339


013

0431lowastminus0151

0148


0333

0254

0124

0531lowastlowast


nificantat0

05level


nificantat0

01level

CScoarses

andMSmedium

sand

FSfin


eC

carbon

Hhydrogen

Nn

itrogen

Cnidcnidaria


podaO


gastro

tricha


oidaN

emnem

atod

aTu

rbturbellaria




d


J1015840



13

0

Freq

uenc

y

minus008

minus006

minus004

minus002

0020

004

006

008

01

012

014

016

018

02

022

024

026

BEST

Rho







Olygo

Others

Kinor Isop

Turb

HrpcGastro

Nem

Poly

Cnid 2D Stress 008

2040

6080

Similarity



0

50

100

150

200

250

300

350

0

2

4

6

8

10

12

14

Nem

atod

e co

pepo

d ra

tio

NC ratioCopepods

Cop

epod

s100

ccm

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veil




4 Conclusion




Acknowledgments


References

























































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in



ofinterstitialtaxaa

ndhydrograph

icandsedimentp

aram

eterso

fthe

study

area

Meio

Temp

pHSal

DO

CSMS

FSPartS

CH

NNem

Poly

Oligo

Turb

Hrpc

Gastr

Kino

rIsop

Cnid

Others

Meio

1Temp

0025

1pH

0301

0126

1Sal

0177

0132minus0372lowast

1DO

0001


1CS


0458lowastminus0303

1MS

0376lowast

0172minus0081

0168

0266minus0415lowast

1FSminus0410lowast

0081


1PartS



0769lowastlowast



0038

0132minus0308


0152

0266

1Hminus0184

0492lowastlowast

0017


023

minus021

0161minus0328

1N

0241


0607lowastlowast

0225

0059minus0062

002

0098

004

10233

1Nem


0121

007minus006

80263

0114

minus0315

0353

0076minus0433lowast

0037

1Po

ly0304

000

60378lowast



000

9012

1Oligo

017minus0171



0093

0327

1Tu



0396lowastminus032



0119

1Hrpc

0794lowastlowast

0292

0359


044

1lowastminus0338

0117minus0265

0109

031

0327

0386lowast

0016

0116

1Gastr

0677lowastlowast

0226

0291


0217minus0216


0231

0555lowastlowast

0236minus0021

0433lowast

0480lowastlowast

1Kino

r0633lowastlowast

0079

0085

0153

0291minus0026

0244minus0235


0286

0396lowastminus0101

02

0430lowast

0414lowast

0117

1Isop

064

8lowastlowast

0078

0078

0161

0262minus0013

0262minus0264


022

0288minus0091

016

0113

0643lowastlowast

0049

0781lowastlowast

1Cn

id0513lowastlowast

0071minus0008

0071

0217

0176

0031minus0164


0197


0088

0521lowastlowast

0003

0639lowastlowast

0422lowast

0169

1Others


0261

0285

000

40322minus0339


013

0431lowastminus0151

0148


0333

0254

0124

0531lowastlowast


nificantat0

05level


nificantat0

01level

CScoarses

andMSmedium

sand

FSfin


eC

carbon

Hhydrogen

Nn

itrogen

Cnidcnidaria


podaO


gastro

tricha


oidaN

emnem

atod

aTu

rbturbellaria




d


J1015840



13

0

Freq

uenc

y

minus008

minus006

minus004

minus002

0020

004

006

008

01

012

014

016

018

02

022

024

026

BEST

Rho







Olygo

Others

Kinor Isop

Turb

HrpcGastro

Nem

Poly

Cnid 2D Stress 008

2040

6080

Similarity



0

50

100

150

200

250

300

350

0

2

4

6

8

10

12

14

Nem

atod

e co

pepo

d ra

tio

NC ratioCopepods

Cop

epod

s100

ccm

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veil




4 Conclusion




Acknowledgments


References

























































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in




d


J1015840



13

0

Freq

uenc

y

minus008

minus006

minus004

minus002

0020

004

006

008

01

012

014

016

018

02

022

024

026

BEST

Rho







Olygo

Others

Kinor Isop

Turb

HrpcGastro

Nem

Poly

Cnid 2D Stress 008

2040

6080

Similarity



0

50

100

150

200

250

300

350

0

2

4

6

8

10

12

14

Nem

atod

e co

pepo

d ra

tio

NC ratioCopepods

Cop

epod

s100

ccm

Cher

ai

Fort

Koc

hi

Art

hung

al

Sakt

hiku

lang

ara

Veil




4 Conclusion




Acknowledgments


References

























































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in


4 Conclusion




Acknowledgments


References

























































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in































2waste off the












Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in










Volume 2014

Mining


Journal of



Geophysics







Journal of




Advances in











Geology Advances in

research article ecology of interstitial faunal assemblage ...along the coast of kerala, india...

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