Identification of optimum scopes of environmental factors for snails using spatial analysis techniques in Dongting Lake ...

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Title:
Identification of optimum scopes of environmental factors for snails using spatial analysis techniques in Dongting Lake Region, China
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English
Creator:
Wu, Jin-Yi
Zhou, Yi-Biao
Li, Lin-Han
Zheng, Sheng-Bang
Liang, Song
Coatsworth, Ashley
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Bio Med Central (Parasites & Vectors)
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Abstract:
Background: Owing to the harmfulness and seriousness of Schistosomiasis japonica in China, the control and prevention of S. japonica transmission are imperative. As the unique intermediate host of this disease, Oncomelania hupensis plays an important role in the transmission. It has been reported that the snail population in Qiangliang Lake district, Dongting Lake Region has been naturally declining and is slowly becoming extinct. Considering the changes of environmental factors that may cause this phenomenon, we try to explore the relationship between circumstance elements and snails, and then search for the possible optimum scopes of environmental factors for snails. Methods: Moisture content of soil, pH, temperature of soil and elevation were collected by corresponding apparatus in the study sites. The LISA statistic and GWR model were used to analyze the association between factors and mean snail density, and the values in high-high clustered areas and low-low clustered areas were extracted to find out the possible optimum ranges of these elements for snails. Results: A total of 8,589 snail specimens were collected from 397 sampling sites in the study field. Besides the mean snail density, three environmental factors including water content, pH and temperature had high spatial autocorrelation. The spatial clustering suggested that the possible optimum scopes of moisture content, pH, temperature of the soil and elevation were 58.70 to 68.93%, 6.80 to 7.80, 22.73 to 24.23°C and 23.50 to 25.97 m, respectively. Moreover, the GWR model showed that the possible optimum ranges of these four factors were 36.58 to 61.08%, 6.541 to 6.89, 24.30 to 25.70°C and 23.50 to 29.44 m, respectively. Conclusion: The results indicated the association between snails and environmental factors was not linear but U-shaped. Considering the results of two analysis methods, the possible optimum scopes of moisture content, pH, temperature of the soil and elevation were 58.70% to 68.93%, 6.6 to 7.0, 22.73°C to 24.23°C, and 23.5 m to 26.0 m, respectively. The findings in this research will help in making an effective strategy to control snails and provide a method to analyze other factors. Keywords: Schistosomiasis japonica, Oncomelania hupensis, Environmental factors, Spatial clustering, GWR
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Wu et al. Parasites & Vectors 2014, 7:216 http://www.parasitesandvectors.com/content/7/1/216; Pages 1-12
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doi:10.1186/1756-3305-7-216 Cite this article as: Wu et al.: Identification of optimum scopes of environmental factors for snails using spatial analysis techniques in Dongting Lake Region, China. Parasites & Vectors 2014 7:216.

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RESEARCHOpenAccessIdentificationofoptimumscopesofenvironmental factorsforsnailsusingspatialanalysistechniques inDongtingLakeRegion,ChinaJin-YiWu1,2,3,Yi-BiaoZhou1,2,3*,Lin-HanLi1,2,3,Sheng-BangZheng1,2,3,SongLiang4,5,AshleyCoatsworth6, Guang-HuiRen7,Xiu-XiaSong1,2,3,ZhongHe8,BinCai9,Jia-BianYou10andQing-WuJiang1,2,3AbstractBackground: Owingtotheharmfulnessandseriousnessof Schistosomiasisjaponica inChina,thecontroland preventionof S.japonica transmissionareimperative.Astheuniqueintermediatehostofthisdisease, Oncomelania hupensis playsanimportantroleinthetransmission.IthasbeenreportedthatthesnailpopulationinQiangliangLake district,DongtingLakeRegionhasbeennaturallydecliningandisslowlybecomingextinct.Consideringthechanges ofenvironmentalfactorsthatmaycausethisphenomenon,wetrytoexploretherelationshipbetweencircumstance elementsandsnails,andthensearchforthepossibleoptimumscopesofenvironmentalfactorsforsnails. Methods: Moisturecontentofsoil,pH,temperatureofsoilandelevationwerecollectedbycorrespondingapparatus inthestudysites.TheLISAstatisticandGWRmodelwereusedtoanalyzetheassociationbetweenfactorsandmean snaildensity,andthevaluesinhigh-highclusteredareasandlow-lowclusteredareaswereextractedtofindoutthe possibleoptimumrangesoftheseelementsforsnails. Results: Atotalof8,589snailspecimenswerecollectedfrom397samplingsitesinthestudyfield.Besidesthe meansnaildensity,threeenvironmen talfactorsincludingwatercontent, pHandtemperaturehadhighspatial autocorrelation.Thespatialcluste ringsuggestedthatthepossibleoptimumscopesofmoisturecontent,pH, temperatureofthesoilandelevationwere58.70to68.93%,6.80to7.80,22.73to24.23Cand23.50to25.97m, respectively.Moreover,theGWRmodelshowedthatthepossibleoptimumrangesofthesefourfactorswere 36.58to61.08%,6.541to6.89,24.30to25.70Cand23.50to29.44m,respectively. Conclusion: Theresultsindicatedtheassociationbetweensnailsandenvironmentalfactorswasnotlinearbut U-shaped.Consideringtheresultsoftwoanalysismet hods,thepossibleoptimumscopesofmoisturecontent, pH,temperatureofthesoilandelevationwere58.70%to68.93%,6.6to7.0,22.73Cto24.23C,and23.5mto 26.0m,respectively.Thefindingsinthisresearchwillh elpinmakinganeffectivestrategytocontrolsnailsand provideamethodtoanalyzeotherfactors. Keywords: Schistosomiasisjaponica Oncomelaniahupensis ,Environmentalfactors,Spatialclustering,GWR *Correspondence: z_yibiao@hotmail.com1DepartmentofEpidemiology,SchoolofPublicHealth,FudanUniversity,138 YiXueYuanRoad,Shanghai200032,China2KeyLaboratoryofPublicHealthSafety,MinistryofEducation,Fudan University,138YiXueYuanRoad,Shanghai200032,China Fulllistofauthorinformationisavailableattheendofthearticle 2014Wuetal.;licenseeBioMedCentralLtd.ThisisanOpenAccessarticledistributedunderthetermsoftheCreative CommonsAttributionLicense(http://creativecommons.org/licenses/by/2.0),whichpermitsunrestricteduse,distribution,and reproductioninanymedium,providedtheoriginalworkisproperlycredited.TheCreativeCommonsPublicDomain Dedicationwaiver(http://creativecommons.org/publicdomain/zero/1.0/)appliestothedatamadeavailableinthisarticle, unlessotherwisestated.Wu etal.Parasites&Vectors 2014, 7 :216 http://www.parasitesandvectors.com/content/7/1/216

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BackgroundSchistosomiasis,asnail-borneparasiticdiseaseofpublic health,leadstochronicill-health,withpovertyexacerbating itsnegativehealtheffects.Itaffectsalmost240million peopleworldwide,andmorethan700millionpeople liveinendemicareas[1]. Schistosomiasisjaponica is themosthazardousdiseasetypeofthefivekindsof Schistosomiasis,anditisdifficulttopreventandtreat [2,3]. S.japonica hasexistedinChinaforover2000years, and671.3thousandpeoplewerestillinfectedwith S. japonica until2006insevenprovinces[4-7]. Oncomelaniahupensis ,foundmostlyinmarshlandand lakeareas,isthesoleintermediatehostof S.japonicum .It iscloselyassociatedwiththetransmissionandepidemic of S.japonica .Thedistributionofsnailsisconsistentwith theepidemicareaof S.japonica [8,9].TheThreeGorges Dam(TGD)isoneofseveraltremendousengineering projectstransformingChina ’ secologyandenvironmental circumstance.However,theconstructionofThreeGorges Dam(TGD)andtheimplementationoftheSouth-toNorthWaterDiversionProject(SNWDP)werereported toinfluencethesurroundingecologicalenvironment, whichmightaffectthedistributionofsnails[10-12].Interestingly, Oncomelaniahupensis hasdeclinednaturallyin QiangliangLakedistrict,DongtingLakeRegionsince 1990,andsnailshavenotbeenfoundintheregionsince 2000[13].TheQiangliangLakedistrictislocatedinthe northwesternDongtingLake.Theareaofthisregion wheresnailsusedtoliveandbreedisabout433.2km2. Therefore,thequestionofwhyandhowthisphenomenon ofnaturalpopulationdeclinehasoccurredisundetermined.Thepossibleoptimumscopesofenvironmental factorsforthesnailscapturesourinterest,whichwillhelp explainwhatdrivesthisnaturalpopulationdecline. Withthedevelopmentofspatialtechniques,increasinglymorepublichealthproblemshavebeenanalyzed usingspatialmodeling[12,14-24].Inpreviousresearch, experimentsandfieldtrialshavebothbeenused.Prior analysesoftherelationshipbetweensnailsandenvironmentalfactorscommonlyadoptedaglobalmodel(i.e. ordinaryleastsquareregressionmodel(OLS)),which onlyofferedreliableinformationwithoutconsideringthe spatialvariability.Geographicallyweightedregression (GWR)modelovercamethisproblem,asitmadeuseof spatialinformationadequately[18,25-28].GWRisa newlocalmodelingtechniqueforconductingspatial analysis.Thistechniqueallowslocalasopposedtoglobal modelsofrelationshipstobemeasuredandmapped.The functionisimprovedwithspatialmatrixonthebasisof theOLSmodel.BesidesGWR,LocalIndicatorsofSpatial Association(LISA)wasalsousedtoanalyzethedata.LISA allowsforthedecompositionofglobalindicators,such asMoran ’ sI,intothecontributionofeachindividual observation.TheLISAforeachobservationgivesan indicationoftheextentofsignificantspatialclustering ofsimilarvaluesaroundthatobservation,andthesum ofLISAsforallobservationsisproportionaltoaglobal indicatorofspatialassociation[29].Weutilizedthese techniquestoextractusefulinformationandtoidentify thepossiblesuitablerangesforsnails.Thisstudyaimed toexplorethepossibleoptimumscopesofenvironmental factorsforsnailsusingspatialanalysistechniques(both GWRandLISA)intheirnaturalhabitats.MethodsStudyareaThestudywasconductedinabottomlandofDongting LakeRegion.DongtingLakeislocatedat2830 … 3020 N and11140 … 11340 EinthenortheasternpartofHunan Provinceandcoversawatersurfaceareaof2,681km2. DongtingLakeisthesecondlargestwatersourceinChina andplaysanimportantroleinregulatingwaterlevels intheYangtzeRiver. S.japonica hasbeenendemicin theDongtingLakeregionforcenturies,andithashad adevastatingeffectonthepublichealthofthelocal people[30-36].Abottomlandwith16km2,whichis adjacenttoQiangliangLakedistrict,wasselectedas ourstudyfield(Figure1).ThebottomlandofDongting LakeRegionhasanobviouscharacteristicthatwater arisesinsummerandlandappearsinwinter.Rainfall patternintheareaisseasonal,withtheheaviestrain fallingfromApriltoJuneand thelightestraindropping fromDecembertoFebruary.Thiskindofenvironment isquitesuitableforsnailstoliveandreproduce,meaningthatDongtingLakeRegionhasprovidedoptimal circumstancesfor S.japonica foralongtime[37-41].SnailsamplingSnailsamplingwasconductedfromMay6thtoMay10th in2013toobtainsamplesofsnailsinthebottomlandof DongtingLakeRegion.ThisbottomlandareainDongting LakeRegionhasatypicalenvironmentsuitableforsnail survival.Adoptingsystematicsamplingmethods,snail samplingwasexecutedby10well-trainedcollectorsworkinginthelocalstationforschistosomiasiscontrolforfour days.Weusedtweezersandpaperbagstocollectthe snailsonthesurfaceofbottomland.Thehorizontaland verticaldistancebetweensamplingpointswereboth 20m,andthesamplingareaperpointwasabout0.11m2. Weselected50pointsinthehorizontaldirection,while alsoselecting10linesintheverticaldirection.Thetotal areaofsamplingsiteis10,000m2.Ineachcollection, gatheredsnailswereappropriatelylabeledandtransported tothelaboratoryofthelocalstationforschistosomiasis control. Aftercollection,snailsweretransportedinflasks containing5mlofclear,filteredwater.Afterfourhours, thenumbersofdeadandalivesnailswerecounted.TheWu etal.Parasites&Vectors 2014, 7 :216 Page2of12 http://www.parasitesandvectors.com/content/7/1/216

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waterintheflaskswasusedtomakesmearstoexamine fortheexistenceofcercariaeunderamicroscope.Snails werekilledusingniclosamide.EnvironmentalfactorsamplingSamplingofenvironmentalfactorssimultaneouslycoincidedwithsnailsampling.Whilemeasuringenvironmentalfactors,theweathergenerallyremainedconsistent, providingmostlysunnyweather.Fourelementsincluding watercontent,pH,elevationandtemperaturewerecollectedusingprofessionalequipmentcontainingaGPS handheldPC,amoisturemeter,andapHmeter(which candetectbothpHandtemperature).Allthesefactors weregatheredinthesnailsamplingpoints.Oncerecordingwascomplete,theseparameterswerechecked,and thenmatchedwithmeansnaildensity. WatercontentofsoilwasmeasuredusingaSoilMoistureMeter(SieldScoutTDR300,SpectrumLtd,USA). Theaccuracyofthisinstrumentwas3.0%volumetric watercontent.Theprobeofthemoisturemeterwas putintosoil15cmunderthesurfacetodetectthe watercontent,andthedatawasrecordedwhenthe watercontentreadingwassteady.Aftertheprocessof collectingthedata,alltheinformationwouldbeexported intoacomputer.Tomakethedataaccurate,adjustment forsoilmoisturewasneeded.Thirtysamplingpointswere randomlyselectedfromthesnailsamplingpoints,to collectsamplesofsoilweighing30gin15cmdeepfor soilmoistureassessment.Soilsampleswereplacedinto aplasticcontainertopreventthechangeofproperties insoil.Thewatercontentofthesesamplingsoilswas testedusingthedryingmethod[42].Finally,acalibration curvewascalculated,andalltheinformationofwater moisturecorrectedaccordingly. TemperatureandpHofsoilweremeasuredwithPortable WaterproofpH/ORP/CMeter(HANNAHI991002N, HannaInstrumentsLtd,Italy).Theaccuracyofthisequipmentwas1Coutsideand0.02pH.Theglassprobe ofthemeterwasputintosoil15cmunderthesurface, andthedatawasrecordedwhenthereadingwassteady. Beforethenextmeasurement,theglassprobewaswashed bydistilledwater.ToobtainthepHvalue,wecollected the15cmdeepsoilweighing30g(thenumberofsoil samplingwas30)toputintoaplasticcontainer.Thesoil wasdissolvedby25mlsoilsamplepreparationsolution (HANNAHI7051,HannaInstrumentsLtd,Italy).The pHmeterwasusedtodetectthesoilsuspension.From theserecordings,calibrationcurvewascalculatedand datacorrected. ElevationwasmeasuredwithGPShandheldPC(TRIMBLEGeoExplorer3000Ge oXMHandheld,Trimble NavigationLtd,USA).Theaccuracyofdetectingelevationis10cmwithanexternalantenna(Trimble Zephyr2,TrimbleNavigationLtd,USA).Thisantenna offersprecisepositioningwithsub-millimeterphase centeraccuracyandarobust low-elevationsatellite tracking.Beforethecollectionofelevation,thelevelof signalswasatleastsixsatellites.Theelevationand Figure1 LocationofsampledbottomlandinDongtingLakeRegion. Detailedlegends:Thismapshowswherethesampledbottomlandis locatedin. Wu etal.Parasites&Vectors 2014, 7 :216 Page3of12 http://www.parasitesandvectors.com/content/7/1/216

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geographiccoordinatesysteminformationwasautomaticallywrittenintothemeterafterinitiatingtherecording andkeepingthedevicestillfor15seconds.Thedatawas thenexportedintoacomputertogenerateamap,using ArcGIS10.0(EnvironmentalSystemsResearchInstitute, Inc.,Redlands,CA).StatisticalanalysisUsingGeoDa1.4.0(SpatialAnalysisLaboratory,University ofIllinois,Urbana-Champaign,IL,USA,https://geodacenter.asu.edu/),wefirstcalculatedtheunivariateLISA indicatorofsnailstoproduceaLISAclustermapofthe bottomlandofDongtingLakeRegion.Intheprocedureof calculation,wechosequeencontiguityasthecontiguity weight. Spatialclusteringofthesnailswaschecked.Thedata yieldedspatialclusters(positiveautocorrelation)falling intotwocategories(High-HighandLow-Low)andtwo classesofoutliers(negativeau tocorrelation,High-Lowand Low-High).InferenceforallMoran ’ sIstatisticsisbased onpermutationtesting,whereareferencedistribution iscalculatedforspatialrandomnessandcomparedwith theobserveddataovermultipleiterations[43]. InthecalculationofLISA,pvalues<0.05wereconsideredstatisticallysignificant.Thiswastheunifiedtest criterioninthefollowingcomputations.Thetheoryof thisstatisticisasfollows:LocalIndicatorsofSpatialAssociation,LISAThelocalautocorrelationstatisticsforeachobservation isdefinedasthefollowingform:[29] Ii ZiXjWijZjZiand Zjaredeviationsfromthemean,whichare standardizedz-scoresforeachvariableiandj,respectively. ThestandardizedZ-scoreforeachvariableiscomputedas theobservedvalue(e.g.,watercontent)atlocationiminus themeanratefortheneighborsj(e.g.,averagewater content)dividedbythestandarddeviation.Thesummationover j issuchthatonlytheneighboringvalues j J areincluded.Inthisresearch, IidenotestheLISA indexofpervariableinpoint i and Wijisthedistancebasedspatialweightmatrixrevealingtheproximityof point i topoint j TheclusteringdegreerisesasLISAvalueincreases. AnareawithhighLISAvalueisaclusteredareathat shouldbenoticed.Therearefourassociationpatterns, includinghigh-high,high-low,low-highandlow-low. High-highandlow-lowpatternsrevealthatthevaluein onepointissimilarwiththataroundit.High-lowand low-highillustratesthatvalueinonepointhasdifferent neighboringvalues. Second,wecalculatedunivariatestatisticsandMoran ’ s Istatisticofeachvariabletocheckdistributionandto measurespatialautocorrelation.AdoptingGeoDa1.4.0. PositivevaluesofMoran ’ sIstatisticrevealsthatneighbouringpointshavesimilarvaluesandviceversa.Spatial modelsaresuitableforvariableswithsignificantspatial autocorrelation. Third,sincedependentvalueandmeansnaildensitywas notgaussiandistributed,weusedsquarerootmethodto transformit.Anordinaryleastsquares(OLS)regression modelwasfittedtoestimatetheassociationofenvironmentalfactorsandmeansnaildensity.Thisstepwas conductedinIBMSPSS19.0(IBMCorporation,USA). Colinearitywasmeasuredbycomputingvarianceinflation factor(VIF).ColinearitycouldbeneglectedifVIFisless than10. Owingtotheexistenceofspatialautocorrelation,geographicallyweightedregression(GWR)moreaccurately analyzedtheassociationbetweenenvironmentalfactors andmeansnaildensity.WeusedGWR4.0(Professor TomokiNakaya,TheDepartmentofGeography,RitsumeikanUniversity,Kyoto,Japan,http://www.st-andrews. ac.uk/geoinformatics/)toanalyzetheassociation.Inthe processofcalculation,gaussianmodelandfixedgaussian kerneltypewereadopted.Wechoseanappropriatespatial weightingfunctionbasedonAIC.Thelinearmodeland GWRmodelwerecompared.IfthedifferenceofAICin thesetwomodelswasmorethanthree,GWRwouldbe utilizedasthebettermodel,evenconsideringthecomplicacyofGWR.Thetheoryisasfollows:Geographicallyweightedregression,GWRYidenotesthedependentvariable, K representsthenumberofvariables, i isthenumberofsamples; 0isa primaryparameter, iisthespatialerrorinpoint i, andthe correspondingcoefficientestimateis= (XTX) 1XTY .The functionisasfollowing: Yi 0ui; vi X kui; vi kik i( ui, vi)isthecoordinateofcentralpoint.Inthisstudy, Yiisthemeansnaildensityinpoint i;kikiskthenvironmentalfactorinpoint i ,wherethesubscript k denotes thecountofenvironmentalelements;and iistheresidual error. k( ui, vi)representsthevalueofcontinuousfunction k( u v )inpoint i .InGWR[44],regressioncoefficientis notaglobalunifiedvalue,butaparameterthatwill changeindifferentlocations.Theseestimatesbasedon geographicalspacedescribehowtheparameterchanges withthevariationofspace.Therefore,wecanexplorethe spatialheterogeneityinthesevariables. Fourth,valuesinthepointspossessingspatialclustering wereextracted.Univariatestatisticsweredisplayedaccordingtotwogroups(high-highandlow-low).Similarly,Wu etal.Parasites&Vectors 2014, 7 :216 Page4of12 http://www.parasitesandvectors.com/content/7/1/216

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weextractedsignificantpointsintheGWRmodeland analyzedunivariatestatisticsintwogroups(positive correlationandnegativeassociation). Finally,interquartilerangesinthesetwotablesofenvironmentalfactorswerecomparedwiththereportedreferencescopessuitableforsnailhabitationandreproduction.ResultsUnivariateanalysesInthisstudy,atotalof8,589snailspecimenswerecollectedfrom397samplingsites.Therangeofsnaildensity was0to148snailsper0.11m2,andthemeanvaluewas 23.58withastandarddeviationof24.82.Aftersquareroot transformation,therangechangedtobe0to12.17,and themeanvaluebecame5.79withastandarddeviationof 2.99.Therefore,thetransformationmadethedependent variableapproachgaussiandistribution. Therangeofhumiditywasfrom0.07%to0.99%,and themeanvalueofitwas0.67%withthestandarddeviation of0.26%;theaveragevalueofelevationwas27.97m withthestandarddeviationof6.11masitsrangewas from18.45to52.67m.TheoverallrangeofpHwas from5.23to8.70withameanvalueof6.77andthe standarddeviationof0.37;theaveragevalueoftemperature was24.36Cwithitsrangefrom20.20to32.10Candthe STDof1.80C. Boththemeansnaildensityanditstransformedvalue hadhighspatialautocorrelation(bothMoran ’ sIvalues were0.50),demonstratingthatsamplingpointswithhigh snaildensitytendedtobelocatedclosetoothersimilar highvaluepoints. Besidesthemeansnaildensity,threeenvironmental factorsincludingwatercontent,pHandtemperaturehad highspatialautocorrelation.Elevationwasmuchlower, butitwasalsospatiallyautocorrelated.SpatialdistributionofsnailsFigure2showsthelocalspatialpatternofmeansnail density.High-highandlow-lowlocationsweretypically spatiallyclustered,whilehigh-lowandlow-highlocations arespatialoutliers.ItwasworthnoticingthatLISAcluster maponlyreferstothecoreofthecluster.Theclusterwas classifiedassuchwhenthevalueatalocationismore similartoitsneighborsthanwouldbethecaseunder spatialrandomness.Theclusteringofhigh-highmean snaildensitywaslocatedinthemiddleregionofthe bottomlandstudyarea,whiletheclusteringoflow-low meansnaildensitywasmainlysituatedatthemarginof thebottomland(Figure1).MultivariateanalysesTable1presentstheresultsofthefullregression model.Sinceallthevarianceinflationfactorsofindependentvariableswerebelow10,multicollinearitywas notproblematic.Amongfourparameters,watercontent andpHwerestatisticallysignificant,showinganegative associationwithmeansnaildensity.Elevationandtemperaturehadnostatisticalsignificance. Figure2 LISAclusterofmeansnaildensityinabottomlandofDongtingLakeRegion. Detailedlegends:Thismapshowsthespatial clusterlocations. Wu etal.Parasites&Vectors 2014, 7 :216 Page5of12 http://www.parasitesandvectors.com/content/7/1/216

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ThefitoftheOLSmodelwasnotgood(Loglikelihood=-8,AIC=1743.82,AdjustedR2=0.13).Thehigh probabilitiesoftheJarque-Berascoreindicatedgaussian distributionoftheerror.LowprobabilitiesofWhitetest, Breusch-PaganandKoenker-Bassettscoresshowedthe existenceofheteroskedasticity(P<0.05).Moran ’ sI(error) scorewaspositiveandhighlysignificant(P<0.05),indicatingastrongpositivespatialautocorrelationofthe residuals. Asthedependentvariableandindependentvariables werespatiallyautocorrelatedandlocallydistributed,we usedgeographicallyweightedregression(GWR)toanalyze theassociationbetweenthem.IntheGWRmodel,every samplingpointwouldproduceaspecifiedmodelcontainingcoefficientsanditsp-value.ComparedwithOLS model,theregressioncoefficientschangedconsiderably. Environmentalfactorshadbothnegativeassociationand positiveassociationwiththesquarerootofmeansnail density,asdifferentsamplingpointshadvaryinglocal conditions.Atthesametime,thesignificanceofthefour covariatesalsochanged. Table2revealstheresultsoftheGWRmodel.ContrastingthemodelfitpartinOLSandGWRmodels,it wascertainthatGWRperformedbetter.InthediagnosticassessmentofGWR,theresultsdemonstratedthat GWRwasbetterthanglobalspatialregressionmodels. ThelowpossibilityofGWRANOVAtestreportedthat GWRhadsomeimprovements.ThesignificantFstatistic resultingfromtheANOVAtestwasutilizedtoestablish whethertheGWRmodelprovidesabetterfitoverthe globalregressionmodel,andthesevaluessupporttheuse ofGWR.TheDIFFofCriterionwastheresultofatestof spatialvariabilityinavariable ’ scoefficient(basedonan AICcriterion).DIFFoffourindependentvariableshad negativevalues,indicatingthatGWRwasbetterthan globalanalysis.DOFwasthedegreeoffreedominthe ANOVAanalysis.Collectively,GWRwasestablishedas agoodperformingmodelforthesevariables. Tofurtherillustratethecoefficientsandtherelevant P-valueinGWRmodel,GWRparametermapsofeach covariatewereconstructed.Inthenorthwesternpartof thestudiedbottomland,theGWRmapofwatercontent (Figure3)indicatedthat,themeansnaildensitywas positivelyassociatedwithwatercontentwhentherange ofthecoefficientwasfrom1.50to3.78.Themapillustratedthatanincreaseofwatercontentmightgenerate anincreaseinmeansnaildensityinacertainarea. Meanwhile,itsuggestedthattherelationshipbetween watercontentandsnailswaspositivebutnotlinear. Table1OLSregressionmodel:associationbetweenmean snaildensityandnaturalcharacteristicsinDongtingLake RegionModelFit R2AdjustedR2LoglikelihoodAIC 0.140.13 866.911743.82 ModelEstimation VIF SDtP Constant17.043.385.050.00** Water-content(%)1.46 0.030.01 3.780.00** Elevation(m)1.160.020.030.750.45* PH1.45 1.300.48 2.720.01** Temperature(C)1.26 0.130.09 1.410.16* DiagnosticTests TestsDFValueP NormalityoferrorsJarque-Bera20.030.99 HeteroskedasticityBreusch-Pagan412.970.01 Koenker-Bassett421.060.00 White1454.990.00 SpatialdependenceMoran ’ sI(error)0.4814.790.00**P<0.05,*P>0.05. Table2GWRmodels:associationbetweenmeansnail densityandnaturalcharacteri sticsinDongtingLakeregionModelFit R2AdjustedR2LoglikelihoodAIC 0.740.651305.351446.73 ModelEstimation t MinMaxMeanSTDMinMaxMeanSTD Constant2.147.285.111.322.8019.6011.653.64 Water-content (%) 5.453.18 0.612.10 8.076.44 0.944.30 Elevation(m) 1.891.16 0.020.49 4.232.620.021.22 PH 2.020.86 0.170.59 3.552.45 0.201.17 Temperature(C) 1.520.72 0.100.42 3.862.10 0.210.99 DiagnosticTests GWRAnovaTable SSDFMSFP GlobalResiduals2717.145.00 GWR Improvement 1901.6788.2721.54 GWRResiduals815.48262.733.106.94<0.05 Geographicalvariabilitytestsoflocalcoefficients FDOFforFtestDIFFof Criterion Constant4.192.83 8.61 Watercontent7.393.20 25.92 Elevation5.773.28 12.03 PH6.843.31 15.74 Temperature279.513.07 388.96 Wu etal.Parasites&Vectors 2014, 7 :216 Page6of12 http://www.parasitesandvectors.com/content/7/1/216

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Threeotherfactorshadstatisticallysignificantpositive associationswithmeansnaildensityintheareas.The rangesofcoefficientswerefrom0.42to0.86(pH,Figure4), from0.35to0.72(temperature,Figure5),andfrom0.57to 1.16(elevation,Figure6).SuitablerangeanalysesAccordingtotheresultsoftheLISAclusteranalysis,snail habitatsweredividedintohigh-highclusteredareasand low-lowclusteredareas.Therefore,asillustratedinTable3, fourenvironmentalfactorsweredividedintohigh-high andlow-lowgroupsrespectively.Sinceallthefactors didnotfollowgaussiandistribution,inter-quartilerange wasabetterparametertoillustrateahospitablerangefor snailsurvival. Theinter-quartilerangeofhigh-highclusteredareain watercontentwasfrom58.70%to58.93%,suggestingthat snailswouldsurviveandreproducelargelyinthatregion. Similarly,theinterquartilerangeofthelow-lowclustered areawasfrom70.00%to99.90%.Thelow-lowclustered areaindicatedthatsnailswouldnotthriveinthisarea. Forinter-quartilerangeofelevation,thescopeof high-highclusteredareawasfrom23.50mto30.39m, whiletherangeoflow-lowclusteredareawasfrom 25.97mto34.60m.Forinter-quartilerangeofpH,the rangeofhigh-highclusteredareawasfrom6.56to6.85, asthescopeoflow-lowclusteredareawasfrom6.93to 7.20.Fortemperature,therangeofhigh-highclustered areawasfrom22.73Cto24.28C,whilethescopeof low-lowclusteredareawasfrom25.10Cto25.83C. Table4presentsthatwatercontentispositivelyassociatedwithmeansnaildensitywhenthewatercontentis between36.58%and61.08%.However,thisrelationship wasnegativelyassociatedwhenwithintherangeof66.60% to99.90%.Similarly,elevationandmeansnaildensity hadpositivecorrelationwhenelevationrangewasfrom 24.79mto29.44m,andtheyhadnegativecorrelation whenelevationrangewasfrom21.85mto25.25m.PH andmeansnaildensitywerepositivelycorrelatedinpH rangefrom6.54to6.89,butwerenegativelycorrelated inpHrangefrom6.73to7.05.Temperatureandmean snaildensityhadpositiveassociationastemperature scopewasfrom24.30Cto25.70C,whilethenegative scopewasfrom22.40Cto24.15C.DiscussionOncomelaniahupensis istheuniqueintermediatehost of S.japonica inChina,anditsdistributionishighly consistentwiththe S.japonica epidemicarea[45].The survival,reproductionandspreadofthesesnailsareoften influencedbymanyfactors,andamongtheseelements, environmentalfactors(i.e.climate,hydrology,vegetation, andsunlight)playasignificantrole[46].Inmanypast studies,theeffectsofthesefactorsonsnailshavealone Figure3 CoefficientandsignificanceofwatercontentinGWRmodel. Detailedlegends:Thismapshowsthevalueofparametersandits significanceinGWRmodeltoillustratehowwatercontentinfluencesmeansnaildensity. Wu etal.Parasites&Vectors 2014, 7 :216 Page7of12 http://www.parasitesandvectors.com/content/7/1/216

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Figure5 CoefficientandsignificanceoftemperatureinGWRmodel. Detailedlegends:Thismapshowsthevalueofparametersandits significanceinGWRmodeltoillustratehowtemperatureinfluencesmeansnaildensity. Figure4 CoefficientandsignificanceofpHinGWRmodel. Detailedlegends:Thismapshowsthevalueofparametersanditssignificancein GWRmodeltoillustratehowpHinfluencesmeansnaildensity. Wu etal.Parasites&Vectors 2014, 7 :216 Page8of12 http://www.parasitesandvectors.com/content/7/1/216

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beenanalyzedinalaboratorysetting[46-50]orafield [51,52].However,thesefactorshaveinteractionssothat occasionalsynergeticeffectscanbegenerated[53].Hence, wedetectedthefourmainenvironmentalfactors(i.e. watercontent,pH,temperatureofsoilandelevation)in thebottomlandofDongtingLakeRegion,andincluded thesefourelements,intothespatialmodeltoanalyzethe complexcollectiveeffectsoftheelementsonsnails.Our resultsshowedthatsnailshadobviousspatialclustering areasinthebottomland(high-highclusteringareasare locatedinthenorthwesternbottomland,whilelow-low clusteringareasarelocated inthesoutheasternbottomland).Thisfindingofthespatialclusterofsnailswas consistentwithpreviousreports[54,55].Basedonthis finding,therangesoftheenvironmentalfactorsinthese high-highclusteredareasofsnailsmightbethesuitable rangesforthesesnails,whilethescopesofcircumstance elementsinthelow-lowclusteredareaspossiblygenerate unsuitablerangesforsnails.Accordingtothishypothesis, wediscussedthepossibleoptimumscopes.Meanwhile, weusedtheGWRmodeltoanalyzetheassociation betweensnailsandenvironmentalfactors,sowecould provideanalternativemeansofidentifyingthepossible optimumrangesforthesnails. Theresultsofthisstudyshowedthattherangeof 58.70%to68.93%wasthemoisturecontentscopeinthe Figure6 CoefficientandsignificanceofelevationinGWRmodel. Detailedlegends:Thismapshowsthevalueofparametersandits significanceinGWRmodeltoillustratehowelevationinfluencesmeansnaildensity. Table3Univariatestatisticsoftheindependentvariables offourclustersinDongtingLakeRegionNMedianPercentilesPercentiles (25%)(75%) Watercontent(%)High-High4465.9058.7068.93 Low-Low5499.9099.9099.90 Elevation(m)High-High4426.6623.5030.39 Low-Low5427.8725.9734.60 PHHigh-High446.656.566.85 Low-Low547.056.937.20 Temperature(C)High-High4423.5022.7324.28 Low-Low5425.4025.1025.83 Table4Univariatestatisticsoftheindependentvariables oflinearcorrelationinGWRinDongtingLakeRegionNMedianPercentilesPercentiles (25%)(75%) Watercontent(%)positive11852.3036.5861.08 negative18579.2066.6099.90 Elevation(m)positive2427.6024.7929.44 negative1824.1221.8525.25 PHpositive76.696.546.89 negative306.936.737.05 Temperature(C)positive425.0024.3025.70 negative1323.6022.4024.15 Wu etal.Parasites&Vectors 2014, 7 :216 Page9of12 http://www.parasitesandvectors.com/content/7/1/216

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high-highclusteredareasofsnails,whileinthelow-low clusteredareas,mostofthewatercontentvalueswere 99.90%,withsomevaluesbeingbelow30.00%.Therefore, snailsmightnotsurvivewhenwatercontentofsoilis morethan99.90%orlessthan30.00%.Thisindicatedthat meansnaildensityandmoisturecontenthadaU-shaped association,thussnailswouldliveandbreedinthisgiven waterrange.Snailsmightstarttomigrateoutoftheir habitatifwatercontentwasoutofthissuitablescope. Chen etal. [56]reportedthatasmallnumberofsnails begantomovewhenwatercontentwasmorethan 12.00%,aboutonefifthsnailswouldstartmovingat 20.00%watercontent,abouthalfofsnailswouldmoveat 30.00%watercontent,andthesnailswouldbeveryactive at40.00%watercontent.However,whenwatercontent wasmorethan80.00%,meansnaildensitywoulddecline [56].Similarly,theassociationinGWRmodelshowedthat themeansnaildensityincreasedgraduallywhenthe waterscopewasbetween36.58and61.08%,whilethey decreasedgraduallyastherangewasfrom66.60to99.90%. Thesefurthersupportedourpre viousresults.Considering theoutcomesofpastandcurrentexperiments,wesupposedthat58.70%to68.93%mightbeasuitablerangeof watermoistureinsoilforthesnailsinourstudysite. Inthehigh-highclusteredareasofsnails,theelevation wasfrom23.50mto30.39m,whileinthelow-lowclusteredregions,theelevationwasfrom25.97mto34.60m. Thesetwokindsofclusteredrangesofelevationhadsome interactions,anditmightberelatedtoonlytheelevation consideredandotherfactorsmaynotbeinvolved.When thefourfactorswereanalyzedtogetherintheGWR model,ourresultsshowedthatthemeansnaildensity increasedgraduallywhentheelevationwasfrom24.79m to29.44m,whilethemeansnaildensitydecreased graduallywhentheelevationwasfrom25.25mto 21.85m.Previouslyreportedrangesfromstudiesbeing conductedineasternDongtingLakeRegioninclude optimalelevationsof24.50mto26.00minDongkou [51]and25.00mto27.50minMatang[52].Basedon theresultsofthepreviousliteratureandthisstudy, 23.5mto26.0mmightbeanoptimumscopeofthe elevationforsnailsinourstudyfield. TheresultsofpHshowedthathigh-highclusteredrange wasfrom6.56to6.85,andlow-lowclusteredrangewas between6.93and7.20.Therangesofhigh-highclustered andlow-lowclusteredwerebothintherange6.7to 7.8,asreportedinTable5.TheresultsofGWRmodel highlightedthatthemeansnaildensityincreasedgradually whenthepHwasbetween6.54and6.89,whilemeansnail densitydecreasedgraduallywhenthepHwasfrom6.73to 7.05.Basedontheresultsofthepreviousreportsandthis study,6.6to7.0mightbeasuitablerangeofpHforsnails inthisstudyfield. Thehigh-highclusteredrangeoftemperaturewasfrom 22.73Cto24.28C,asthelow-lowclusteredscopeofthat wasfrom25.10Cto25.83C.Su etal .(1963)reportedthat snailsurvivalwouldbethreatenedifthetemperaturewas lessthan5.00Cormorethan35.00C,andthesnail wouldnoteatfoodpastthoseparameters[58].Theresults oftheGWRmodelpresentedshowthatthemeansnail densityincreasedgraduallywhenthetemperaturewas between24.30Cand25.70C,whilemeansnaildensity decreasedgraduallywhenthetemperaturewasfrom 24.15Cto22.40C.Consideringtheresultsinthisstudy andpreviousstudies,apossiblesuitablerangeoftemperaturewasfrom22.73Cto24.23Cinourstudysite.Itis worthnotingthatuncertaintyexistedintheprocessof modelfitting. Theoptimumtemperaturerangeinthisstudypresented anarrowerrangeincomparisontopriorliterature.This differencemightbeattributedtoanewmethodapplied duringourstudy.Incontrasttopreviousresearch,informationofenvironmentalfactorswascollectedinour studysites,whereasdataofenvironmentalelementswere gatheredinlaboratoriesamongpreviousstudies.Thedata wasthenanalyzedbylocalindicatorsofspatialautocorrelationandspatialregressionmodel,whichtookthespatial attributesintoaccount.Inpreviousliterature,descriptive methodsandlinearmodelswerecommonlyadopted. However,somelimitationsmayexistwiththesepast Table5ReportedrangesoffourenvironmentalfactorssuitableforsnailexistenceAuthor/dateMethodReferencrange Water-content(%)Temperature(C)PHElevaton(m) OuYang etal. 2009[ 57 ]Survey-13~25-Xu etal. 2001[ 49 ]Experiment4020~30-Wang etal .2007[ 47 ]Experiment-20~30-Hu etal .2010[ 52 ]Survey---25.0~27.5 Lu etal .2013[ 48 ]Experiment-20~25-Luo etal. 2012[ 51 ]Survey---24.5~26.0 Yang etal .2009[ 46 ]Experiment3020~266.7~7.8Zhou etal. 2005[ 50 ]Experiment-20~256.8~7.5Wu etal.Parasites&Vectors 2014, 7 :216 Page10of12 http://www.parasitesandvectors.com/content/7/1/216

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approaches.First,experimentaldatamightnotreflect therealsituationinthesamplingsites,sincethedelivery ofsamplesandmicroenvironmentinalaboratorymight changethecontentinthesamples.Second,descriptive methodsandlinearmodeldidnotconsiderthespatial clusteringinsnailsintheprocessofanalysis. Severallimitationswerehighlightedinourstudy.First, thesamplingofsnailsandenvironmentalelementswere conductedonlyinsummer.Furtherstudiescouldbecarriedoutduringspringinthesamepositions.Second,our studywasmainlycarriedoutinbottomlandandwater. Thesamplingsitescouldbeexpandedinfutureresearch.ConclusionInsummary,thisresearchconductedafieldsurvey,collecteddatainthesamplingsitesandanalyzedthedata usingspatialtechniques.Comparedwithpreviousreports, theexplorationsinthisstudy adoptedfieldresearchinstead ofexperimentalandusedanewmethodtoanalyzedata. Naturalfactorsofthesoilmightdecidesnailsurvival,and therelationshipbetweenmeansnaildensityandnatural factors(e.g.,moisturecontent)wasnonlinear.Indeed,it followsaU-shapedcurveasthesnailsdonotseemto survivewhenthesoilwatercontentiseitherextremely high(99.9%)orlessthan30%,leadingtosnaildispersion outsidetheoptimalrangeof59%-69%.Thesefindings mightcontributetobetterpredictionandcontrolofsnail habitatdynamics,leadingtomoreaccuratepreventionof S.japonica transmission.Competinginterests Allauthorsdeclarethattheyhavenocompetinginterests. Authors ’ contributions YZ,GRandQJconceivedthestudy;JW,YZ,GR,LL,SZ,XS,ZH,BC,JY,andQJ performedthefieldcollections;JW,SL,ACandYZwrotethemanuscript;JW performedstatisticalanalyses.Alltheauthorsreadandapprovedthefinal versionofthemanuscript. Acknowledgements ThisworkissupportedbyNationalNaturalScienceFoundationofChina(No. 30590374),theNationalS&TMajorProgram(GrantNo.2012ZX10004-220 and2008ZX10004-011),andShanghaiLeadingAcademicDisciplineProject (ProjectNo.B118). Authordetails1DepartmentofEpidemiology,SchoolofPublicHealth,FudanUniversity,138 YiXueYuanRoad,Shanghai200032,China.2KeyLaboratoryofPublicHealth Safety,MinistryofEducation,FudanUniversity,138YiXueYuanRoad, Shanghai200032,China.3CenterforTropicalDiseaseResearch,Fudan University,138YiXueYuanRoad,Shanghai200032,China.4Departmentof EnvironmentalandGlobalHealth,CollegeofPublicHealthandHealth Professions,UniversityofFlorida,Gainesville,FL,USA.5EmergingPathogens Institute,UniversityofFlorida,Gainesville,FL,USA.6Departmentof Epidemiology,CollegeofPublicHealthandHealthProfessions,Universityof Florida,Gainesville,FL,USA.7HunanstationforSchistosomiasisControl, Changsha,HunanProvince410000,China.8JunshanofficeofLeadingGroup forSchistosomiasisControl,Yueyang,Hunanprovince414000,China.9JunshanstationforSchistosomiasisControl,Yueyang,HunanProvince 414000,China.10QianlianghustationforSchistosomiasisControl,Yueyang, HunanProvince414000,China. 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Submit your next manuscript to BioMed Central and take full advantage of: € Convenient online submission € Thorough peer review € No space constraints or color “gure charges € Immediate publication on acceptance € Inclusion in PubMed, CAS, Scopus and Google Scholar € Research which is freely available for redistribution Submit your manuscript at www.biomedcentral.com/submit Wu etal.Parasites&Vectors 2014, 7 :216 Page12of12 http://www.parasitesandvectors.com/content/7/1/216