Hierarchy theory reveals multiscale predictors of Arkansas ......River basin, a tributary of the Arkansas River in southcentral Kansas, U.S.A. (Figure 1). Average annual precipitation

Freshwater Biology 201964659ndash670 wileyonlinelibrarycomjournalfwb emsp|emsp659copy 2019 John Wiley amp Sons Ltd

Received21April2018emsp |emsp Revised21November2018emsp |emsp Accepted2December2018DOI101111fwb13252

O R I G I N A L A R T I C L E

Hierarchy theory reveals multiscale predictors of Arkansas darter (Etheostoma cragini) abundance in a Great Plains riverscape

Juju C Wellemeyer1emsp|emspJoshuah S Perkin2emsp|emspMary Liz Jameson3emsp|emspKatie H Costigan4emsp|emsp Ryan Waters5

1MissouriDepartmentofConservationResourceScienceDivisionMaitlandMOUSA2DepartmentofWildlifeandFisheriesSciencesTexasAampMUniversityCollegeStationTXUSA3DepartmentofBiologicalSciencesWichitaStateUniversityWichitaKSUSA4SchoolofGeosciencesUniversityofLouisianaatLafayetteLafayetteLAUSA5KansasDepartmentofWildlifeParksandTourismEcologicalServicesSectionPrattKSUSA

CorrespondenceJoshuahSPerkinDepartmentofWildlifeandFisheriesSciencesTexasAampMUniversityCollegeStationTXUSAEmailJPerkintamuedu

Funding informationTexasAampMUniversityNationalInstituteofFoodandAgricultureGrantAwardNumber1017538KansasDepartmentofWildlifeParksandTourism

Abstract1 Landscapeecologyanditsemphasisonrelationshipsbetweenspatialheterogene-ityscaleandecologicalprocessescanbeappliedtomanagestreamecosystemsasriverscapesHierarchytheoryacentraltenetofriverscapeecologyallowsforinvestigatingecologicalrelationshipsbetweenaquaticorganismsandhabitatbyexploring the nested interactions inherent in reaches segments and basinsArkansasdarterEtheostoma craginiisaGreatPlainsfishendemictotheArkansasRiverbasinandislistedasinneedofconservationinallfivestateswithinitsrangeinNorthAmericaTheaimofthisstudywastodevelopempiricalmodelsdescrib-ing relationships between Arkansas darter abundance and local habitats andidentifytheappropriatescale(s)forassessingandmanagingpopulations

2 WeusedArkansasdarterabundancedatacollectedfromstreamsampleunitsasafixedgrainsize(102m)andcompileddatasetsatthreehierarchicalspatialextentsincludingreach(103m)nestedwithinsegment(104m)nestedwithinbasin(105m)insouthcentralKansasWefitgeneralisedlinearmixedmodels(GLMMs)toassessscale-specificrelationshipsbetweenArkansasdarterabundanceandlocalhabitatdimensions(streamdepthandwidth)andheterogeneity(canopycoveroverhang-ingvegetationandwoodystructure)

3 Habitatparametersincludedinbest-supportedGLMMsdifferedamongextentsVariation in Arkansas darter abundance was explained by canopy cover andchannel depth at the reach (54 explained) and segment (56) extents andstreamwidthanddepthatthebasinextent(37)PartialdependenceplotsfrommultipleregressionGLMMsrevealedthatArkansasdarterabundancewasnega-tively correlated with increasing channel depth across all extents increasingcanopycoveratreachandsegmentextentsandincreasingchannelwidthatthebasinextent

4 Ourresultshighlightscale-specificrelationshipsbetweenArkansasdarterabun-danceand localhabitatsacrossmultiplespatialextentsThesefindingsprovidedirection forassessingstreamfishecologypattern-process relationshipsat the

660emsp |emsp emspensp WELLEMEYER Et aL

1emsp |emspINTRODUC TION

Landscape ecology emphasises relationships between spatial het-erogeneityscaleandecologicalprocessesCentraltenetsofland-scape ecology include consideration of the processes that createandmaintain spatial heterogeneity the influenceof scale on eco-logical interactionsandhowmanagementofspatialheterogeneityregulatesecologicalprocesses(Turner19892005)Amajorthemeinlandscapeecologyistheapplicationofhierarchytheorytodecou-ple complex systems into smaller components as ameans of sim-plifyingresearchofwholesystems(AllenampStarr2017Wu2013)Thisispossiblebecauseanecologicalsystemthatoperatesasatruehierarchycanbecharacterisedasa system of systems within systems (King 1997) For example foraging by herbivores occurswithin anestedhierarchy inwhich local feedingstationsarenestedwithinlarger plant community patches and patches are in turn nestedwithinbroader landscapeandregionalsystems(Senftetal1987)Theprinciplesoflandscapeecologyincludinghierarchytheoryareapplicable to stream ecosystems despite the implicit reference toland(Wiens2002)InfactFrissellLissWarrenandHurley(1986)andFauschTorgersenBaxterandLi (2002)describedthenestedhierarchy of stream habitats including microhabitats (10minus1 to 0m)nestedwithinchannelunitssuchaspoolsorriffles(101ndash2m)nestedwithin reaches (102ndash3m)nestedwithinsegments (103ndash5m)nestedwithinstreamsystems(otherwiseknownasbasins105ndash6m)Theseandother studies (LabbeampFausch2000)highlighted theprocessofviewingstreamnetworksasriverscapehierarchiestoinvestigatemultiscalevariablesthatregulateorganismabundanceanddistribu-tionRiverscapeperspectivesareincreasinglyappliedtochallengesfacing conservation of biodiversity in aquatic ecosystems (ErősOHanleyampCzegleacutedi2018Fausch2010)

Assessing the riverscapeecologyof fishes in theGreatPlainsUSA isofcriticalconservation interestbecausehabitatdiversityiscommonlysimplifiedbyanthropogeniclandscapealterationsop-eratingacrossmultiplescalesDroughtandfloodingarenaturalhy-drologicdisturbances intheGreatPlainsandcauseexpansionandcontractionof theheterogeneity and scaleof riverscapes (DoddsGidoWhiles Fritz ampMatthews 2004 Stanley Fisher ampGrimm1997)HoweveranthropogenicmodificationstoGreatPlainsriver-scapeshavedisruptednaturalpatternsinspatialheterogeneitywithnegativeconsequencesforecologicalprocesses involvingendemicfishes (Hoagstrom BrooksampDavenport 2011)Multi-scale alter-ationstoecologicalprocessesresultincompetitionwithnon-nativespeciesacrosslocalhabitats(GidoSchaeferampPigg2004LabbeampFausch2000)degradationofwaterqualityacrossreaches(Cross

1950) altered hydrologic regimes across segments (Costigan ampDaniels2012)andfragmentationofhydrologicconnectivity(PerkinampGido 2011Worthington BrewerGrabowskiampMueller 2014)and dewatering of streams and aquifers (Perkin Gido CostiganDanielsampJohnson2015PerkinGidoCooperetal2015Perkinetal 2017) across basins These multi-scale alterations requiremulti-scaleassessmentsofconservationstatusparticularlyforre-gionallyendemicArkansasdarterEtheostoma craigini(seeoverviewbyLabbeampFausch2000)InthestateofColoradoArkansasdarterconservationactionsnowconsiderpool-scalehabitatrefuge(SmithampFausch1997)reach-scalehabitatconnectivity(GroceBaileyampFausch2012)andsegment-scalepopulationstructure(FitzpatrickCrockett amp Funk 2014) Despite abundant research in ColoradoArkansasdarterhasdeclined locally throughoutmuchof its rangebecauseofchangestoGreatPlainsriverscapes(USFishandWildlifeService2016) suggestingadditional research isnecessary toplanconservationactionsinvolvingmulti-scaleenvironmentalregulatorsofArkansasdarterabundance

Empirical models describing relationships between Arkansasdarter abundance and habitat dimension and heterogeneity arenecessary to inform conservation actions Habitat dimension canbemeasuredasstreamwidth(m)anddepth(m)whereasheteroge-neityinvolvesstructuressuchasaquaticvegetationcanopycoverandinstreamwoodystructureEachofthesecomponentsofhabitatisregulatedbyhydrologicprocessesthatlinkstreamstoterrestriallandscapes (BurcherValettampBenfield2007PerkinTroiaShawGerkenampGido2016)Forexampleterrestrialhabitattransforma-tion has disrupted historic vegetative succession regimes and al-lowedforwoodyencroachmentacrossbasins (Briggsetal2005)andthisaffectsstreamreachesandsegmentsbystabilisingbanksincreasingstreamdepthsclosingotherwiseopencanopiesandde-positing instreamwoodystructure (Fischeretal2010Poffetal1997)Whetherornotandtowhatextent thesehabitatchangesaffectArkansasdarterabundancehasnotbeeninvestigated(EberleampErnsting2014)Furthermoreabundance-basedmodelsarecrit-ical because conservation and restoration goals are routinely setaround abundance data and descriptivemodels provide some ex-pectation for the benefits associated with specific conservationactionsDependingonthenatureofrelationshipshabitatscanbemanipulatedtobenefitfishabundancesthroughpracticessuchasri-pariantreeplantingsorremovalsatfinescalesaswellascoordinatedlandusepracticesacrossbroaderscales (KwakampFreeman2010)Simultaneousassessmentoftheappropriatehabitatdimensionsandheterogeneityacrossspatialscaleswillhighlighttheappropriateac-tionsandspatialextentsforimplementinghabitatpreservationand

appropriatespatialscalesandbenefitnativefishconservationbyhighlightingtheapplicationofhierarchytheorytoaddressmanagementchallenges

K E Y W O R D S

conservationbiologyfishecologylandscapeecologyscalingstreamsandrivers

emspensp emsp | emsp661WELLEMEYER Et aL

restorationtobenefitconservationofArkansasdarter(Fauschetal2002)

ThegoalofthisstudywastoevaluateenvironmentalgradientsthatregulateArkansasdartercatchrate(fishhr)acrossmultiplespa-tialscalesto informconservationandmanagementofthespeciesTo accomplish this goal we used principles of landscape ecologyandhierarchytheorytodocumentrelationshipsbetweenpatternsinArkansasdartercatchrateandhabitatdimensionaswellashetero-geneityatthreenestedspatialextents(reachsegmentandbasin)Wetestedtwohypotheses(1)thatrangesofvaluesforhabitatvari-ablesandArkansasdarterabundanceweregreateratbroaderspatialextentscomparedtofinerspatialextentsand(2)thatrelationshipsbetweenhabitatandabundancewouldbestrongestat thebroad-estspatialextenttested(iebasin)Thesehypothesesarebasedonknown correlations between increases in environmental gradientsand increases in the role of environmental factors in constrainingfishdistributions (JacksonPeres-NetoampOlden2001) andmorerecent evidence for greater environmental (as opposed to disper-sal)effectsonorganismsinaquaticsystemsatspatialextentsthatapproximate basins (Heino etal 2015) Our objectives included

(1) quantifying local habitat gradients across scales (2) describingrelationshipsbetweenArkansasdartercatchrateandhabitatvari-ablesacrossbroadeningspatialextentsand (3) framingmultiscaleinteractionsamongenvironmentalprocesseswithinthecontextofhierarchytheory

11emsp|emspStudy area

We assessed multi-scale relationships between habitat heteroge-neityandArkansasdarterabundanceintheSouthForkNinnescahRiverbasinatributaryoftheArkansasRiverinsouthcentralKansasUSA (Figure1) Average annual precipitation for this region is775mmandaverageannualairtemperatureis139degC(HousemanKrausharampRogers2016)TheSouthForkNinnescahRiverisasand-bedbraidedperennialrivercharacterisedbydecreasingbedslopebutincreasingwidthanddepthinadownstreamdirection(CostiganDanielsPerkinampGido2014)The flowregime in theSouthForkNinnescahRiverisunregulatedandthenativefishassemblagere-mainslargelyintactdespitehistoricallossesofsomespeciesduringdroughtperiods(PerkinampGido2011PerkinGidoCostiganetal

F I G U R E 1emspStudyareamapillustratingmultiplespatialextentsatwhichrelationshipsbetweenhabitatvariablesandArkansasdartercatchratesweretestedincluding(a)reach(b)segmentand(c)basinextentsForallextentssampleunits(greycircles)representtheconsistentgrainsizeatwhichobservationsofhabitatanddartercatchrateweremade(d)TheextentofArkansasdarterrangeAcrossallpanelsblackstreamsrepresenttheembeddedlocationofthenextsmallerspatialextent


2015)ThelargesttributarytotheSouthForkNinnescahRiverisafourth-order segment of streamknown as SmootsCreek SmootsCreek flows southeast to join the South ForkNinnescah just up-streamoftheconfluencebetweentheSouthandNorthforksandastypicalforGreatPlainsstreamsofitssizeSmootsCreekisgen-erally perennial but is subject to drying during periods of intensedrought(Doddsetal2004)NestedwithinthesegmentofSmootsCreekisareachofstreamthatflowsthroughthe063km2GerberReserveoperatedbyWichitaStateUniversityTheGerberPreservewashistoricallygrazedbycattlebutreducedgrazingandlackofac-tivelandmanagementresultedinencroachmentofnativeandnon-nativetreesduringrecentdecades(Housemanetal2016)In2010prairierestorationwasinitiatedwithmanagedgrasslandburningandtreeremovalwhichcreatedagradientofwoodyencroachmentneartheupstreamextentoftheGerberPreservethattransitionedtore-storedprairiegrasslandtowardsthemiddleanddownstreamextentofthereserve

2emsp |emspMETHODS

21emsp|emspScales of investigation

We tested for relationships between Arkansas darter abundanceandstreamhabitatparametersusingaconsistent(iefixed)spatialgrain and three spatial extentsGrain size is defined as the finestspatialresolutionofstudyandisthescaleatwhichobservationsareconducted (Wiens 1989)Weuse sample units asour grain (sensu StoddardampHayes2005)definedhereasalengthofstream(102m)selectedbasedonaccessavailabilitytocrewsandsurveyedinacon-tinuousmanner to assess fish communities and habitat attributesatallspatialextentsSpatialextentisdefinedasthespatialdimen-sionoverwhichallobservationsareconducted(Wiens1989)Weuse three spatial extents of increasingmagnitude including reach(103m) segment (104m) and basin (105m) These spatial extentstheir assigned labels and their scalemagnitudes reflect thosede-scribedbyFrisselletal(1986)LabbeandFausch(2000)andFauschetal (2002)The reachspatialextentconsistedof10consecutivesampleunitsdistributed longitudinallyalongSmootsCreekontheWichita StateUniversityGerber Preserve in KingmanCounty KS(lat 376760deg lon minus979461deg Figure1a) The segment spatial ex-tentconsistedoffivesampleunitsdistributedalongSmootsCreek(Figure1b) The basin spatial extent consisted of 37 sample unitsdistributedalongtheSouthForkNinnescahRiver(Figure1c)EachofthesespatialscalesencompassesaportionofthecorerangeofArkansasdarter(Figure1d)

WecompiledfishsurveydatausingindependentdatasetsforeachspatialextentThereachspatialextentwassampledbytheauthors at the beginning of three consecutive summer months(JuneJulyAugust)during2014and2015(ietemporalextentof2years)Tensampleunitswereeachrepeatedlysampledsixtimesfor a total of60observations at the reachextent The segmentspatialextentwassampledbytheKansasDepartmentofWildlifeParks and Tourism (KDWPT) Ecological Services Stream Survey

andAssessment Program once during the summer for five con-secutiveyearsduring2005ndash2009(ietemporalextentof5years)Fivesampleunitswereeachrepeatedlysampledfivetimesforatotalof25observationsatthesegmentextentThebasinspatialextentwassampledbytheKDWPTonceduringsummermonthsfor20consecutiveyearsduring1994ndash2005(ietemporalextentof20years)Thirty-sevensampleunitsweresampledonetoninetimesforatotalof97observationsatthebasinextentWedidnotmix datasets across spatial extents for this study meaning thatsamples from the reachextentwerenot included in segmentorbasinextentanalysesandthatsamplesfromthesegmentextentwerenotincludedinthebasinextentanalysisThisscalingstrat-egy isdescribed indetailbyAllenandStarr (2017) and involvesusingpredefinedscalesherebasedonpreviousriverscape liter-ature(Fauschetal2002Frisselletal1986)toinvestigatethemannerinwhichecologicalpatternschangeasscalesareallowedtovary

22emsp|emspArkansas darter capture rate

Fish surveys includedmonitoring using a combination of electro-fishingandseiningDetailedprotocolsaredescribed inLazorchakKlemmandPeck(1998)andincludedsingle-passelectrofishingofallavailablehabitatsatasampleunitinanupstreamdirectionandsein-ingonlydeeperhabitatsinadownstreamdirectionThisapproachisknowntoyieldreliableestimatesoffishabundancesinGreatPlainsprairiestreamsandiscomparabletomoreintensivemulti-passpro-cedures(BertrandGidoampGuy2006)Largestreamsweresampledwithtotebargeelectrofishingandseiningwhilebackpackelectro-fishingwasusedinsmallstreamsandthelengthoftimespentelec-trofishingorseiningwasrecordedAllcollectedfisheswereheldateachsiteuntiltheywereidentifiedtospeciesandthenreleasedbackinto the habitat fromwhich theywere captured Arkansas dartercaptureratewascalculatedasthenumberofdarterscollectedperhouroftimespentsampling(iefishhr)ateachsampleunitAsin-glesamplecollectedbytheKDWPTwasremovedfromanalysisbe-causeitincludedarecordnumberofArkansasdarter(n=2136)andresultedinanextremevalueforcapturerate(2959fishhr)Captureratewasthenusedastheresponsevariableinmodelconstructionforeachspatialextentincludedinthisstudy

23emsp|emspLocal habitat data

We includedmeasurements of local habitat dimension and heter-ogeneity as potential descriptors ofArkansas darter capture rateHabitatvariableswerecollectedduring the samesamplingeventsascaptureratedataanddetailedmethodsareprovidedinLazorchaketal (1998) Briefly habitat sampling included measurements ofstreamwidthdepthcanopycoverinstreamwoodystructureandbankvegetationusing10evenlyspacedtransectsdistributedalongeach sample unit At each transect the wetted width (m) of thestreamwasrecordedanddepth(m)wasmeasuredatfivepointsdis-tributedevenlyalongthetransectlineAtthecentrepointofeach


transectaconcavedensiometerwasusedtorecordcanopycoverbystandinginthestreamandfacingupstreamAlongeachtransecttheproportionofareacoveredbyinstreamwoodystructurewithaminimumdiameterof7cmat thebase (woody structurehereafter)andoverhangingbankvegetation(vegetationhereafter)wasvisuallyestimatedMultiplehabitatmeasurementscollectedforeachsampleunitweresummarisedbytheirmeanincludingmeandepth(channeldepth)meanwettedwidth(channelwidth)andmeancanopycover(canopy)

24emsp|emspData analyses

We compared univariate gradients in environmental variablesandArkansasdartercaptureratesacrossscalesusingprobabil-itydensity functions to testour firsthypothesis thatgradientsincrease with spatial extent Probability density functions areparticularlyuseful for assessingdistributionswhennon-normaldistributionsareexpectedanddonotrequirebinningdataWeused the smdensitycompare function from the sm package inR (R Core Team 2016) with 10000 bootstrapped samples totestequalityofdatadistributionsforvegetationstreamdepthwoodystructurecanopycoverandstreamwidthacrossreachsegmentandbasinextents(BowmanampAzzalini2014)Wealsoassessed differences in time spent sampling (ie electrofishingand seining measured in s) and Arkansas darter capture rates(fishhr) across extentsWe first conducted three-way tests ofequalityforeachvariableandifsignificantdifferencesoccurred(p lt 005 α=005) we assessed pairwise differences acrossscales (ie three pairwise possibilities) based on overlappingconfidence intervals The three-way test was a permuted testof equality across density estimates groupedby spatial extentand95confidence intervalsprovidedby the functionsmden-sitycompareallowedforassessingpairwisedifferenceswhenthepermuted testwas significantWe illustrated variable distribu-tionsusingdensitykernelsandasterisks tosummarisepost hoc pairwisecomparisons

Prior tomodel fitting andhypothesis testingwe assessed thepresenceofautocorrelationandcorrelationamonghabitatvariablesWetestedforspatialautocorrelationamongvariablesmeasuredatthefinestspatialextent(reach)becausemeasurementstakenclosetogether in space are more likely to correlate (Legendre 1993)Autocorrelationfunctionsappliedusingtheacf inR illustratedtheabsenceof spatial autocorrelation for all parametersexcept chan-nelwidth (Supporting Information Figure S1) Significant negativespatialautocorrelationamongwidthsoccurredonlyduringasinglevisit and only at a single distance (Supporting Information FigureS1) Given these patterns we proceededwith statistical analyseswithoutincorporatingadjustmentsforspatialautocorrelationNextwe assessed pairwise correlations among habitat variables usingthecorrplot function inR (WeiampSimko2017)This initial test re-vealedsomelevelofcorrelationamonghabitatvariables(SupportingInformation Figure S2) indicating that any subsequent model-ling should include consideration ofmulticollinearity (Mansfieldamp

Helms1982)andrelyonmodelselectionmethodsthatavoidissuesofmulticollinearity(Graham2003)

Wefitgeneralisedlinearmixedmodels(GLMMs)andusedmodelselectiontoquantifyrelationshipsbetweenArkansasdartercapturerateand localhabitatparametersatreachsegmentandbasinex-tents to testoursecondhypothesis thatmodels fitatbroaderex-tendsdescribemorevariationForeachextent independentlywebuilt16competingmodelswithArkansasdarter catch rateas theresponse variable and intercept-only channel depth (m) channelwidth(m)canopycover(proportion)woodycover(proportion)veg-etation cover (proportion) and all possible two-way combinationsofthesevariablesaspredictors(Table1)Wedidnotincludemorecomplexmodels(eg3ndash5-termmodels)becausesamplessizeswereinsufficientForeachmodelweused repeatedvisits (sitevisit) tosampleunitsthroughtimeasarandomvariableallowedinterceptsandslopestovaryrandomlyemployedaPoissonerrordistributionand z-score transformed all predictor variables to better approxi-matenormaldistributionsWefitGLMMsusingtheglmerfunctionfromthe lme4packageinRandcomparedmodelsusingAkaikein-formationcriterionadjusted for small samplesize (AICc)using thesemmodelfits function from the piecewiseSEM package (Lefcheck2015)WeassessedmodelfitusingmarginalR2valuedescribedbyNakagawa and Schielzeth (2013) because this value describes thevarianceexplainedbyfixedfactorsinthemodel(iepureenviron-mentaleffects)Weillustratedscale-specificrelationshipsbetweenArkansas darter capture rate and habitat parameters included inbest-supportedmodelsusingpartialdependenceplotsandthesjpglmer functionfromthesjPlotpackage (Luumldecke2017)Finallyal-thoughAICcmodelselection involvingallpossiblesubsetsofvari-ablesisanacceptedmethodforavoidingissuesofmulticollinearity(Graham 2003) we assessed multicollinearity in best-supportedmodelsusingconditionnumber(K)andvarianceinflationfactor(VIF)asdescribedindetailbyAlin(2010)Asgeneralprinciplesmulticol-linearity isnotconsideredproblematicatK lt 5andVIFlt10 (Alin2010)AllstatisticswereconductedinRversion332(RCoreTeam2016)

3emsp |emspRESULTS

Gradients for predictor variables sampling effort and Arkansasdartercatchratevariedwithspatialextentbutrangesofonlychan-nelwidth increased as hypothesised Environmental variables andArkansasdartercapturerateswerecollectedduringatotalof182samplingoccasionsDistributionsofobservedvaluesforvegetationcoveragedifferedamongextents(probabilitydensitytestp lt 001)and attenuated with increased spatial extent (Figure2a) whilestreamdepth(p = 009)andwoodystructure(p = 011)distributionswereconsistentamongextents(Figure2bc)Canopycoverdifferedamongextents(p lt 001)butwassimilarbetweensegmentandbasinextents(Figure2d)Streamwidthsdifferedamongallthreeextents(p lt 001Figure2e)Timespentsamplingincreasedwithspatialex-tent (p lt 001 Figure2f) however Arkansas darter capture rates


TA B L E 1emspScalesandstructuresforgeneralisedlinearmixedmodelsselectedatreach(n=60observations)segment(n=25)andbasin(n=97)extentsillustratingAICcdelta-AICcAkaikeweightsandr-squarevaluesformodelsusedtodescriberelationshipsbetweenlocalhabitatandArkansasdartercapturerateintheSouthForkNinnescahRiverKSUSA

Scale and model structure AICc ΔAICc wi R2

Reach

1+D+C+(1+D+C|SV) 16759 00 0999 054

1+D+WS+(1+D+WS|SV) 17250 491 lt0001 050

1+WS+C+(1+WS+C|SV) 19157 2398 lt0001 028

1+W+C+(1+W+C|SV) 19458 2699 lt0001 040

1+D+V+(1+D+V|SV) 20541 3782 lt0001 051

1+W+WS+(1+W+WS|SV) 20643 3884 lt0001 029

1+D+W+(1+D+W|SV) 20723 3964 lt0001 038

1+V+C+(1+V+C|SV) 20906 4147 lt0001 044

1+WS+V+(1+WS+V|SV) 21006 4247 lt0001 028

1+C+(1+C|SV) 21220 4461 lt0001 044

1+WS+(1+WS|SV) 21367 4608 lt0001 034

1+D+(1+D|SV) 22723 5964 lt0001 049

1+W+V+(1+W+V|SV) 23859 7100 lt0001 015

1+W+(1+W|SV) 25721 8962 lt0001 011

1+V+(1+V|SV) 26765 10006 lt0001 000

1+(1|SV) 27349 10590 lt0001 000

Segment

1+D+C+(1+D+C|SV) 3887 00 0999 056

1+D+W+(1+D+W|SV) 4022 135 lt0001 045

1+W+C+(1+W+C|SV) 4102 215 lt0001 064

1+W+WS+(1+W+WS|SV) 4483 596 lt0001 065

1+W+V+(1+W+V|SV) 4647 760 lt0001 062

1+D+V+(1+D+V|SV) 4702 815 lt0001 059

1+D+WS+(1+D+WS|SV) 4991 1104 lt0001 069

1+D+(1+D|SV) 5688 1802 lt0001 065

1+V+C+(1+V+C|SV) 6955 3068 lt0001 034

1+WS+C+(1+WS+C|SV) 7689 3802 lt0001 033

1+W+(1+W|SV) 8233 4347 lt0001 049

1+WS+V+(1+WS+V|SV) 8310 4423 lt0001 025

1+V+(1+V|SV) 8951 5065 lt0001 038

1+C+(1+C|SV) 9094 5207 lt0001 040

1+WS+(1+WS|SV) 9117 5230 lt0001 032

1+(1|SV) 11347 7460 lt0001 000

Basin

1+D+W+(1+D+W|SV) 253912 000 0999 037

1+W+WS+(1+W+WS|SV) 288152 34240 lt0001 013

1+WS+C+(1+WS+C|SV) 297048 43136 lt0001 000

1+W+V+(1+W+V|SV) 298539 44627 lt0001 009

1+W+C+(1+W+C|SV) 304779 50866 lt0001 020

1+W+(1+W|SV) 327651 73738 lt0001 040

1+D+C+(1+D+C|SV) 367322 113410 lt0001 002

1+V+C+(1+V+C|SV) 416767 162854 lt0001 006

(Continues)


weregreatestatthereachextent(p lt 001)wheresampletimewasleast(Figure2g)

Relationships between habitat variables and Arkansas dartercaptureratedifferedamongspatialextentsbutmodelfitdidnotin-creasewithspatialextentashypothesisedAtthereachextent54ofvariationinArkansasdatercatchratewasexplainedbychannel

depth and canopy cover therewas strong support for thismodelaboveallothersbasedonAICcandwi values (Table1) andmulti-collinearity was not present (K = 1011 VIF=1026) Reach-scaleArkansasdartercaptureratewasnegativelycorrelatedwithchanneldepth(Figure3a)andcanopycover(Figure3b)Atthesegmentex-tent56ofvariationinArkansasdartercaptureratewasexplained


1+D+V+(1+D+V|SV) 439163 185250 lt0001 001

1+C+(1+C|SV) 458019 204107 lt0001 002

1+D+WS+(1+D+WS|SV) 468114 214201 lt0001 000

1+WS+V+(1+WS+V|SV) 480510 226598 lt0001 004

1+D+(1+D|SV) 487642 233730 lt0001 000

1+V+(1+V|SV) 512335 258422 lt0001 002

1+WS+(1+WS|SV) 569878 315966 lt0001 004

1+(1|SV) 587230 333317 lt0001 000

Modelparametersincludeintercept(1)depth(D)width(W)vegetation(V)woodystructure(WS)canopycover(C)andsitevisit(SVmdasharandomvari-ablerepresentingrepeatedvisits)

TABLE 1emsp (Continued)

F I G U R E 2emspProbabilitydensityfunctionsillustratingextent-specificdistributionsofobservationsfor(a)proportionofareawithoverhangingvegetation(vegetation)(b)channeldepth(c)proportionofareawithwoodystructure(woodystructure)(d)proportionofareawithcanopycover(canopycover)(e)channelwidth(f)samplingtimeand(g)ArkansasdartercapturerateExtentsymbols(reach=Rsegment=Sbasin=B)withmatchingnumbersofasteriskshavesimilardensitydistributions(ienotsignificantlydifferent)andarrowsofcorrespondingcoloursmarkmaximumobservedvalues


bychanneldepthandcanopycover therewas strongsupport forthismodel(Table1)andmulticollinearitywasnotpresent(K = 1261 VIF=1026)Segment-scaleArkansasdartercaptureratewasneg-ativelycorrelatedwithchanneldepth(Figure3c)andcanopycover(Figure3d)Atthebasinextent37ofvariationinArkansasdartercaptureratewasexplainedbychanneldepthandwidththerewasstrongsupportofthismodel(Table1)andmulticollinearitywasnotpresent (K = 1543 VIF=1433) Basin-scaleArkansas darter cap-ture ratewasnegativelycorrelatedwithchanneldepth (Figure3e)andchannelwidth(Figure3f)

4emsp |emspDISCUSSION

Fausch etal (2002) suggested that taking a continuous view ofstreamhabitatsacrossriverscapeswasthebestapproachtobridg-ing the gap between research and conservation of stream fishes

Applicationofhierarchytheoryasameansofdecomposingcomplexsystemsintointeractingpartsorsystems of systems within systemsisacriticalstep inestablishingcontinuousviewsofcomplexecosys-tems such as riverscapes (King1997 Simon1962)Conceptuallythis entails nesting multiple sample units within reaches reacheswithinsegmentsandsegmentswithinbasins(Figure4leftcolumn)ViewingArkansasdarterhabitatassociationsthroughthelensofhi-erarchytheorymeansbasinssuchastheSouthForkNinnescahRivercanbedecomposedintostreamsegmentssuchasSmootsCreekandsegmentsofSmootsCreekcanbedecomposedintoreachessuchastheoneflowingthroughtheGerberReserve(Figure4rightcolumn)In our empirical example reach-scale distribution of sample unitsalonggradientsofchanneldepthandcanopycoverrevealedstrongcorrelationsbetweenthese localhabitatparametersandArkansasdarterabundance Increasing thespatialextentof investigation tothebroadersegmentofSmootsCreekdidnotmodifyobservedvari-ation(iegradientlength)forchanneldepthsalthoughlesscanopycoverwas present among sample units based on probability den-sityanalysesHoweverbothchanneldepthandcanopycoverwereretainedasdescriptorsoflocalabundanceacrossthesegmentandexplainedaconsistentamountofvariation incatchratecomparedto the reachextentScaling-up to thebasin lengthened thegradi-entofstreamwidthsobservedduringsamplingbutchanneldepthsremainedconsistentamongextentsandmeasurementsofhabitatdimension(iewidthanddepth)emergedascorrelatesofArkansasdartercatchrateThesemultiscalefindingsillustratetheapplicationofhierarchytheorytogaingreaterinsightintotheecologyandcon-servationofArkansasdarter

Scale isthe central problem in biologybecauseofuncertainty inhow information is transferredamongdifferinggrainsandextents(Levin 1992) We hypothesised that increasing extent would beaccompaniedby increases ingradient lengths forhabitatvariablesbecauseofinclusionofrarerhabitatsatbroaderextentsWefoundthatscalingbetweenreachsegmentandbasinextentsresultedinincreasinglybroadergradientsonlyforchannelwidthanddepthandamongtheseonlychannelwidthdistributionsdifferedsignificantlyThis pattern reflects the widely documented hierarchical struc-tureofstreamchannelsasdetailedbyHorton (1945)andStrahler(1957) Patterns for other habitat variables including vegetativecoverwoodystructureandcanopycoverhadnoconsistentscalingpatternHowever thesehabitat variables tended tobe correlatedwith eachother For example canopy cover andwoody structurewere strongly correlated (rgt055) across all spatial extents andthese correlations are probably the result of landscape processesthat structure these habitat features Flow pulsesmaintain chan-nel cross-sectional areas (depthandwidth) through theprocessesofsedimentdepositionanderosionbutwoodyencroachmentcanalterdepositionndasherosiondynamicsandcontribute todeeperchan-nelsamongstreamsegmentswithriparianforests (Trimble1997)Trees that exist as a consequence of woody encroachment ulti-mately provide canopy cover and after death are deposited intostreams to create instreamwoody structure (CostiganDanielsampDodds2015)Thusalthoughwoodyencroachment isa long-term

F I G U R E 3emspPartialdependenceplotsfromgeneralisedlinearmixedmodelsfittoArkansasdartercatchrate(fishhr)atreachsegmentandbasinextentsPanelsillustrateestimates(solidlines)and95confidenceintervals(dashedlinesandgreyshades)forpartialdependenceofArkansasdartercatchrateon(a)channeldepthand(b)canopycoveratthereachextent(c)channeldepthand(d)canopycoveratthesegmentextentand(e)channeldepthand(f)channelwidthatthebasinextent


changeinlandscapepatternthegeomorphicprocessesthatinteractwithwoodyencroachmentstructureinstreamhabitatsinamannerthatdoesnotscaleconsistentlywithspatialextent

Therewasnoevidencetosupportoursecondhypothesisregard-ingincreaseinmodelfitatthebasinextentOurdatasuggestthatArkansasdarteroccupyshallowandnarrowheadwaterstreamsandlocationsof the reachand segmentextents included in this studyoverlappedwithheadwaterstreamsScalinguptothebasinextentresultedintheinclusionofotherreachesandsegmentsthatexistedoutsideofareasArkansasdarterisableorwillingtodisperseThissuggestsatrade-offbetweenlocalenvironmentaleffectsinfluenc-ing abundance at finer spatial scales and dispersal limitations in-fluencing occurrence at broader spatial scalesHeino etal (2015)reviewed theeffectof spatial extenton relative influencesof en-vironmentalanddispersalprocessesinregulatingaquaticorganismdistributionsandfoundthatenvironmentaleffects(consideredhere)begin todiminishwhile dispersal effects (not consideredhere) in-creasewithgreaterspatialextentandtheseprocessswitchintheir

dominanceatapproximatelythebasinspatialextentThemostcom-prehensivestudyofArkansasdarterecologysupportssuchatrade-offincludingcorrelatesofoccurrence(spawninghabitatpredation)at broad spatial extents (catchments or basins) and correlates ofabundance (individual andpopulation growth rates) at fine spatialextents(reachesandsegmentsLabbeampFausch2000)Thistrade-off ispotentiallyrelatedtothespace-time correspondence principlewhichstatesincreasesinthespatialscaleofecologicalprocessesareaccompaniedbyincreasesintemporalscale(Wu2013)Inhierarchytheorydynamicsof lower levelsarepredictedtooccuratafasterpacethanhigherlevels(AllenampStarr2017)andpopulationgrowth(anabundancefactor)isafasterprocessthanpopulationestablish-ment(anoccurrencefactor)Futureresearchmightinvestigatetheseprocessesatthescalesidentifiedinthisworkincludingexperimen-talmanipulationsofhabitatheterogeneity (eg instreamstructuremanipulationsHoumljesjoumlGunveBohlinampJohnsson2015)orsimula-tionsinpopulationgrowthratestestedunderarangeofabioticcon-ditions(eghydrologicconnectivityJaegerOldenampPelland2014)

F I G U R E 4emspConceptualdiagramillustratingapplicationofnestedhierarchytheorytoArkansasdarterhabitatassociationsOnthelefthierarchytheoryisconceptuallyshownasnestedcirclesofincreasingsizeandshadingintensitytorepresenthabitatunitsofincreasingspatialextentincludingsampleunit(white)asthespatialgrainsizenestedwithinreach(lightgrey)nestedwithinsegment(mediumgrey)nestedwithinbasin(darkgrey)spatialextentsOntherightthehierarchyofArkansasdarterhabitatassociationsisshownusingthesameprogressionofcolourshadesandspatialscalesScale-specificdescriptorsofArkansasdarterabundanceidentifiedduringmodellingareshownasstreamswithgradientsincanopycoveranddepthforbothreachandsegmentextentsandwidthanddepthforthebasinextentAcrossallspatialextentsArkansasdarterabundancemeasuredatsampleunitsincreasesfromlefttorightorascanopiesopenandstreamsbecomeshalloweratreachandsegmentextentsandasstreamsnarrowandbecomeshalloweratthebasinextent


Despitesignificant relationshipsbetweenhabitatvariablesandArkansas darter capture rates limitations to our study should beconsideredFirstoursampleswereacquiredoverseveralyearsandcollectedbydifferentgroupswhichcanintroducevariationcausedbydifferences insamplingeffortNeverthelesshistoricaldataarecritical inassessingpopulationstabilityoverbroadspatiotemporalextentsandthiscaveatcanbeaddressed(PattonRahelampHubert1998)WetestedforvariabilityofsamplingeffortthroughspaceandtimeandaccountedfordifferencesbyusingcatchrateratherthanabsolutenumberscapturedSecondalthoughwoodystructureandstreamdepthareknowntoinfluencesamplingefficiencyforotherspecies (RosenbergerampDunham2005) thedistributionsof thesevariableswereconsistentacrossextentsinourstudyandthereforewere unlikely to systematically influence cross-scale comparisonsofcapturerateThirdouranalysisutilisedmultiplespatialextentscombinedwithafixedgrainsizetoassessmultiscaleinfluencesoncapturerate(iefocus on scaleasdescribedbyAllenampStarr2017)buttherewasnospatialreplicationofreachessegmentsorbasinsSimilarapproachesemployingafixedgrainsizearecommonlyusedtocontrolforfine-scale(iesampleunitinourcase)variationinob-servational bias (Bartonetal 2013) and the temporal replicationincludedinourmodels(ratherthanspatialreplication)providesin-dicationof thegeneralityofpatternsas inotherstudies (LabbeampFausch2000)Finally eachofourGLMMscontained someunex-plainedvariationsuggestingotherfactorsnotmeasuredduringourstudyormorecomplexmodelsatleastpartlycorrelatewithArkansasdartercapturerate(egwatertemperatureSmithampFausch1997)and could be included in future hierarchical assessments (QuistRahelampHubert2005)Ourstudyprovidesdirectionforthespatialscalesatwhichotherparametersmightbeexploredinfutureworkincludingmeasurementsofhabitatdimensionsatbroaderscalesandmeasuresofhabitatheterogeneityatfinerscales

Anthropogenic alterations to Great Plains riverscapes operateacross spatiotemporal scales to threatenArkansasdarter andourwork suggests that hierarchy theory can inform conservation ac-tionsGroundwater depletion across basins over the past centuryhas reduced the abundance and distribution of the small streamsthat supportArkansasdarter (EberleampErnsting2014Fitzpatricketal 2014 Steward amp Allen 2016) Groundwater is increasinglyconsumedbytheexpandinghumanpopulationanddensitiesofphre-atophytesthatrenderwater inaccessibletofishes (GarbrechtVanLiewampBrown2004Perkinetal2017)Ouranalysessuggestthatthissimultaneousdryingandshadingofheadwaterstreamscreateshabitats that constrainArkansasdarter abundanceConsequentlymaintenanceofsurfacendashgroundwaterconnectionsshouldbeacon-servationprioritytomaintainbaseflowconditionsandavoidextir-pationoffishesdependentupongroundwateroutflows(Falkeetal2011)Maintainingaquifers thatsupportsurfaceflowwillbecomeincreasinglydifficultunderachangingclimaticregimeandArkansasdarterrangeconstrictionscausedbyaquiferdepletionhavealreadyoccurred(EberleampStark2000Perkinetal2017)Atfinerscaleswoody encroachment across segments and reaches has increaseddepths of small stream channels deposition of woody structure

andcanopycover(Briggsetal2005Huxmanetal2005)Ripariancorridorsshouldbemanagedfornativelandscapebuffersincludingthe removal of treeswhere prairie landscapes exist or have beenre-established(egtheGerberReserve)toensureopencanopyandprairie floodplain characteristics persist however trade-offs be-tweenbenefitsandconsequencesofriparianbuffersinagriculturallyaltered landscapesmustbeaddressed (Briggsetal2005Fischeretal 2010)At fine scales such as reaches habitat size gradients(egchanneldepth)shouldbemaintainedsothatmixturesofshal-lowdeepwideandnarrowhabitatsallowforpersistenceofadi-versityoffishesrequiringdifferinghabitatdimensions(TroiaampGido20132014)Thelong-termpersistenceofArkansasdarterpopula-tionsinKansas(GidoDoddsampEberle2010)suggestsprotectionofexistingriverscapeconditionsiscriticalandourapplicationofhier-archytheoryprovidesdirectionforthehabitatfeaturesandscalesthatshouldbetargetedtoenhanceconservationofArkansasdarter

ACKNOWLEDG MENTS

We thank Wichita State University for allowing access to theGerber Reserve as well as Kansas State University and theKDWPT for logistical support Sampling assistance was pro-videdbyWichitaStateUniversity studentE (Dudeck)EngasserKSUstudentsTDavisCPennockMWatersRWeberandBWellemeyerKDWPTFisheryDivision staff JMounts andcrewKDWPTEcological Services staff J Conley and crew andmanyothersAGebhardandtwoanonymousreviewersprovidedhelp-ful feedback during manuscript preparation This manuscriptis contribution 28 of the Wichita State University NinnescahBiological Station Support for JSP was provided by TexasAampMUniversityandbytheUSDANationalInstituteofFoodandAgricultureHATCHProject1017538

CONFLIC T OF INTERE S T

Theauthorshavenoconflictofinteresttodeclare

R E FE R E N C E S

AlinA(2010)MulticollinearityWiley Interdisciplinary Reviews Computational Statistics2(3)370ndash374httpsdoiorg101002wics84

AllenTFampStarrTB(2017)Hierarchy Perspectives for ecological com-plexity(2nded)ChicagoILUniversityofChicagoPresshttpsdoiorg107208chicago97802264897110010001

BartonPSCunninghamSAManningADGibbHLindenmayerD B amp Didham R K (2013) The spatial scaling of beta diver-sity Global Ecology and Biogeography 22(6) 639ndash647 httpsdoiorg101111geb12031

BertrandKNGidoKBampGuyCS(2006)Anevaluationofsingle-passversusmultiple-passbackpackelectrofishingtoestimatetrendsinspeciesabundanceandrichnessinprairiestreamsTransactions of the Kansas Academy of Science109(3)131ndash138httpsdoiorg1016600022-8443(2006)109[131aeosvm]20co2

Bowman AW amp Azzalini A (2014) R package lsquosmrsquo nonparametricsmoothingmethods (version 22-54) Retrieved from httpwwwstatsglaacuk~adriansmhttpazzalinistatunipditBook_sm


Briggs JMKnappAKBlair JMHeisler JLHochGALettMSampMcCarronJK(2005)AnecosystemintransitionCausesandconsequencesoftheconversionofmesicgrasslandtoshrublandBioScience55(3) 243ndash254 httpsdoiorg1016410006-3568(2005)055[0243aeitca]20co2

BurcherCLValettHMampBenfieldEF(2007)Theland-covercas-cadeRelationshipscouplinglandandwaterEcology88(1)228ndash242httpsdoiorg1018900012-9658(2007)88[228tlcrcl]20co2

CostiganKHampDanielsMD (2012)Damming theprairieHumanalteration of Great Plains river regimes Journal of Hydrology44490ndash99httpsdoiorg101016jjhydrol201204008

Costigan K H DanielsM D amp DoddsW K (2015) Fundamentalspatialandtemporaldisconnectionsinthehydrologyofanintermit-tentprairieheadwaternetworkJournal of Hydrology522305ndash316httpsdoiorg101016jjhydrol201412031

Costigan K H Daniels M D Perkin J S amp Gido K B (2014)Longitudinalvariabilityinhydraulicgeometryandsubstratecharac-teristicsofaGreatPlainssand-bedriverGeomorphology21048ndash58httpsdoiorg101016jgeomorph201312017

CrossFB(1950)EffectsofsewageandofaheadwatersimpoundmentonthefishesofStillwaterCreekinPayneCountyOklahomaAmerican Midland Naturalist43(1)128ndash145httpsdoiorg1023072421883

DoddsWKGidoKWhilesMR FritzKMampMatthewsW J(2004)LifeontheedgeTheecologyofGreatPlainsprairiestreamsBioScience54(3) 205ndash216 httpsdoiorg1016410006-3568(2004)054[0205lotete]20co2

EberleMEampErnstingG (2014)Arkansasdarter InKansasFishesCommittee (Ed) Kansas fishes (pp 397ndash399) Lawrence KSUniversityPressofKansas

EberleM E amp StarkW J (2000) Status of the Arkansas darter insouth-central Kansas and adjacent Oklahoma Prairie Naturalist32(2)103ndash114

ErősTOHanley JRampCzegleacutedi I (2018)Aunifiedmodel forop-timizing riverscape conservation Journal of Applied Ecology 55(4)1871ndash1883httpsdoiorg1011111365-266413142

FalkeJAFauschKDMagelkyRAldredADurnfordDSRileyLKampOadR(2011)TheroleofgroundwaterpumpinganddroughtinshapingecologicalfuturesforstreamfishesinadrylandriverbasinofthewesternGreatPlainsUSAEcohydrology4(5)682ndash697httpsdoiorg101002eco158

FauschKD (2010)PrefaceArenaissance instreamfishecology InKBGidoampDAJackson(Eds)Community ecology of stream fishes Concepts approaches and techniques (pp199ndash206)BethesdaMDAmericanFisheriesSocietySymposium73

Fausch K D Torgersen C E Baxter C V amp Li H W (2002)LandscapestoriverscapesBridgingthegapbetweenresearchandconservationof stream fishesBioScience52(6) 483ndash498 httpsdoiorg1016410006-3568(2002)052[0483ltrbtg]20co2

FischerJRQuistMCWigenSLSchaeferAJStewartTWampIsenhartTM(2010)Assemblageandpopulation-levelresponsesofstreamfishtoriparianbuffersatmultiplespatialscalesTransactions of the American Fisheries Society 139(1) 185ndash200 httpsdoiorg101577t09-0501

FitzpatrickSWCrockettHampFunkWC(2014)WateravailabilitystronglyimpactspopulationgeneticpatternsofanimperiledGreatPlainsendemic fishConservation Genetics15(4)771ndash788httpsdoiorg101007s10592-014-0577-0

FrissellCALissWJWarrenCEampHurleyMD(1986)Ahierar-chicalframeworkforstreamhabitatclassificationViewingstreamsinawatershedcontextEnvironmental Management10(2)199ndash214httpsdoiorg101007bf01867358

Garbrecht JVanLiewMampBrownGO (2004) Trends inprecipi-tation streamflow and evapotranspiration in the Great Plains oftheUnitedStates Journal of Hydrologic Engineering9(5) 360ndash367httpsdoiorg101061(asce)1084-0699(2004)95(360)

Gido K B Dodds W K amp Eberle M E (2010) Retrospectiveanalysis of fish community change during a half-centuryof landuse and streamflow changes Journal of the North American Benthological Society 29(3) 970ndash987 httpsdoiorg10189909-1161

GidoKBSchaefer JFampPigg J (2004)Patternsof fish invasionsintheGreatPlainsofNorthAmericaBiological Conservation118(2)121ndash131httpsdoiorg101016jbiocon200307015

Graham M H (2003) Confronting multicollinearity in ecologi-cal multiple regression Ecology 84(11) 2809ndash2815 httpsdoiorg10189002-3114

GroceM C Bailey L L amp Fausch K D (2012) Evaluating thesuccessofArkansasdartertranslocationsinColoradoAnoccu-pancysamplingapproachTransactions of the American Fisheries Society141(3)825ndash840httpsdoiorg101080000284872012680382

HeinoJMeloASSiqueiraTSoininenJValankoSampBiniLM(2015) Metacommunity organisation spatial extent and dispersalin aquatic systems Patterns processes and prospects Freshwater Biology60(5)845ndash869httpsdoiorg101111fwb12533

HoagstromCWBrooksJEampDavenportSR(2011)Alarge-scaleconservationperspective considering endemic fishesof theNorthAmericanplainsBiological Conservation144(1)21ndash34httpsdoiorg101016jbiocon201007015

Houmljesjouml J Gunve E Bohlin T amp Johnsson J I (2015) Addition ofstructuralcomplexityndashcontrastingeffectonjuvenilebrowntroutinanaturalstreamEcology of Freshwater Fish24(4)608ndash615httpsdoiorg101111eff12174

HortonRE(1945)Erosionaldevelopmentofstreamsandtheirdrain-age basins hydrophysical approach to quantitative morphologyGeological Society of America Bulletin 56(3) 275ndash370 httpsdoiorg1011300016-7606(1945)56[275edosat]20co2

HousemanGRKrausharMSampRogersCM(2016)TheWichitaState University Biological Field Station Bringing breadth to re-search along the precipitation gradient in Kansas Transactions of the Kansas Academy of Science 119(1) 27ndash32 httpsdoiorg1016600621190106

HuxmanTEWilcoxBPBreshearsDDScottRLSnyderKASmallEEhellipJacksonRB(2005)Ecohydrologicalimplicationsofwoody plant encroachment Ecology 86(2) 308ndash319 httpsdoiorg10189003-0583

JacksonDAPeres-NetoPRampOldenJD (2001)Whatcontrolswho is where in freshwater fish communities the roles of bioticabioticandspatialfactorsCanadian Journal of Fisheries and Aquatic Sciences58(1)157ndash170

JaegerKLOldenJDampPellandNA(2014)Climatechangepoisedto threaten hydrologic connectivity and endemic fishes in drylandstreams Proceedings of the National Academy of Sciences 111(38)13894ndash13899httpsdoiorg101073pnas1320890111

KingAW (1997)Hierarchy theoryA guide to system structure forwildlifebiologists InJBissonette(Ed)Wildlife and landscape ecol-ogy (pp 185ndash212) New York NY Springer-Verlag httpsdoiorg101007978-1-4612-1918-7

KwakT JampFreemanMC (2010)AssessmentandmanagementofecologicalintegrityInWAHubertampMCQuist(Eds)Inland fish-eries management in North America(3rdedpp353ndash394)BethesdaMDAmericanFisheriesSociety

LabbeTRampFauschKD (2000)Dynamicsof intermittent streamhabitat regulate persistence of a threatened fish at multiplescales Ecological Applications 10(6) 1774ndash1791 httpsdoiorg1018901051-0761(2000)010[1774DOISHR]20CO2

Lazorchak J M Klemm D J amp Peck D V (1998) Environmental Monitoring and Assessment Program Surface Waters Field operations and methods for measuring the ecological condition of wadeable streams WashingtonDCUSEnvironmentalProtectionAgency


Lefcheck J S (2015) piecewiseSEM Piecewise structural equationmodeling in R for ecology evolution and systematicsMethods in Ecology and Evolution7(5)573ndash579

LegendreP (1993)Spatial autocorrelationTroubleornewparadigmEcology74(6)1659ndash1673httpsdoiorg1023071939924

Levin S A (1992) The problem of pattern and scale in ecology TheRobert H MacArthur award lecture Ecology 73(6) 1943ndash1967httpsdoiorg1023071941447

Luumldecke D (2017) sjPlot Data Visualization for Statistics in SocialScience R package version 240 Retrieved fromhttpsCRANR-projectorgpackage=sjPlot

MansfieldERampHelmsBP (1982)DetectingmulticollinearityThe American Statistician36(3a)158ndash160

Nakagawa S amp Schielzeth H (2013) A general and simple methodfor obtaining R2 from generalized linear mixed-effects mod-els Methods in Ecology and Evolution 4(2) 133ndash142 httpsdoiorg101111j2041-210x201200261x

PattonTMRahelFJampHubertWA(1998)UsinghistoricaldatatoassesschangesinWyomingsfishfaunaConservation Biology12(5)1120ndash1128httpsdoiorg101046j1523-1739199897087x

PerkinJSampGidoKB(2011)StreamfragmentationthresholdsforareproductiveguildofGreatPlains fishesFisheries36(8)371ndash383httpsdoiorg101080036324152011597666

Perkin J S Gido K B Cooper A R Turner T F Osborne M JJohnson E R amp Mayes K B (2015) Fragmentation and dewa-tering transform Great Plains stream fish communities Ecological Monographs85(1)73ndash92httpsdoiorg10189014-01211

PerkinJSGidoKBCostiganKHDanielsMDampJohnsonER (2015) Fragmentation and drying ratchet down Great Plainsstream fish diversity Aquatic Conservation Marine and Freshwater Ecosystems25(5)639ndash655httpsdoiorg101002aqc2501

Perkin J SGidoKB Falke J FauschKCrockettH Johnson EampSandersonJ(2017)GroundwaterdeclinesarelinkedtochangesinGreatPlainsstreamfishassemblagesProceedings of the National Academy of Sciences114(8)7373ndash7378httpsdoiorg101073pnas1618936114

PerkinJSTroiaMJShawDCGerkenJEampGidoKB(2016)Multiplewatershedalterations influence fish community structureinGreatPlainsprairiestreamsEcology of Freshwater Fish25(1)141ndash155httpsdoiorg101111eff12198

PoffNLAllanJDBainMBKarrJRPrestegaardKLRichterBDhellipStrombergJC(1997)ThenaturalflowregimeBioScience47(11)769ndash784httpsdoiorg1023071313099

QuistMCRahelFJampHubertWA(2005)Hierarchicalfaunalfil-tersAnapproachtoassessingeffectsofhabitatandnonnativespe-ciesonnativefishesEcology of Freshwater Fish14(1)24ndash39httpsdoiorg101111j1600-0633200400073x

RCore Team (2016)R A language and environment for statistical com-puting Vienna Austria R Foundation for Statistical ComputingRetrievedfromhttpswwwR-projectorg

RosenbergerAEampDunhamJB(2005)Validationofabundanceestimatesfrommarkndashrecaptureandremovaltechniquesforrainbowtroutcapturedby electrofishing in small streams North American Journal of Fisheries Management25(4)1395ndash1410httpsdoiorg101577m04-0811

SenftRLCoughenourMBBaileyDWRittenhouseLRSalaOEampSwiftDM(1987)Largeherbivoreforagingandecologicalhierar-chiesBioScience37(11)789ndash799httpsdoiorg1023071310545

SimonHA (1962)ThearchitectureofcomplexityProceedings of the American Philosophical Society106467ndash482

SmithRKampFauschKD (1997)Thermaltoleranceandvegetationpreference of Arkansas darter and johnny darter from Coloradoplains streams Transactions of the American Fisheries Society126(4) 676ndash686 httpsdoiorg1015771548-8659(1997)126amplt0676ttavpoampgt23co2

StanleyEHFisherSGampGrimmNB(1997)Ecosystemexpansionandcontraction instreamsBioScience47(7)427ndash435httpsdoiorg1023071313058

StewardDRampAllenAJ(2016)PeakgroundwaterdepletionintheHigh Plains Aquifer projections from 1930 to 2110 Agricultural Water Management 170 36ndash48 httpsdoiorg101016jagwat201510003

StoddardMAampHayesJP(2005)TheinfluenceofforestmanagementonheadwaterstreamamphibiansatmultiplespatialscalesEcological Applications15(3)811ndash823httpsdoiorg10189003-5195

StrahlerAN (1957)Quantitativeanalysisofwatershedgeomorphol-ogy Eos Transactions American Geophysical Union38(6) 913ndash920httpsdoiorg101029tr038i006p00913

Trimble S W (1997) Stream channel erosion and change result-ing from riparian forests Geology 25(5) 467ndash469 httpsdoiorg1011300091-7613(1997)025amplt0467sceacrampgt23co2

TroiaMJampGidoKB(2013)Predictingcommunityndashenvironmentre-lationshipsofstreamfishesacrossmultipledrainagebasinsInsightsinto model generality and the effect of spatial extent Journal of Environmental Management128313ndash323httpsdoiorg101016jjenvman201305003

TroiaMJampGidoKB(2014)TowardsamechanisticunderstandingoffishspeciesnichedivergencealongarivercontinuumEcosphere5(4)1ndash18

TurnerMG(1989)LandscapeecologyTheeffectofpatternonpro-cess Annual Review of Ecology and Systematics 20(1) 171ndash197httpsdoiorg101146annureves20110189001131

TurnerMG (2005)LandscapeecologyWhat is thestateof thesci-enceAnnual Review of Ecology Evolution and Systematics36319ndash344httpsdoiorg101146annurevecolsys36102003152614

USFishandWildlifeService(2016)SpeciesstatusassessmentreportforArkansasdarter(Etheostoma cragini)(98pp)

Wei T amp Simko V (2017) R package ldquocorrplotrdquo Visualization of aCorrelation Matrix (Version 084) Retrieved from httpsgithubcomtaiyuncorrplot

Wiens J A (1989) Spatial scaling in ecologyFunctional Ecology3(4)385ndash397httpsdoiorg1023072389612

Wiens J A (2002) Riverine landscapes Taking landscape ecologyinto the water Freshwater Biology 47(4) 501ndash515 httpsdoiorg101046j1365-2427200200887x

WorthingtonTABrewerSKGrabowskiTBampMuellerJ(2014)Backcasting the decline of a vulnerable Great Plains reproductiveecotype Identifying threats and conservation priorities Global Change Biology20(1)89ndash102httpsdoiorg101111gcb12329

WuJ(2013)HierarchytheoryAnoverviewInRRozziSTAPickettCPalmerampJBCallicott(Eds)Linking ecology and ethics for a chang-ing world Values philosphy and action(pp281ndash301)NewYorkNYSpringerhttpsdoiorg101007978-94-007-7470-4

SUPPORTING INFORMATION

Additional supporting information may be found online in theSupportingInformationsectionattheendofthearticle

How to cite this articleWellemeyerJCPerkinJSJamesonMLCostiganKHWatersRHierarchytheoryrevealsmultiscalepredictorsofArkansasdarter(Etheostoma cragini)abundanceinaGreatPlainsriverscapeFreshw Biol 201964659ndash670 httpsdoiorg101111fwb13252


1emsp |emspINTRODUC TION

Landscape ecology emphasises relationships between spatial het-erogeneityscaleandecologicalprocessesCentraltenetsofland-scape ecology include consideration of the processes that createandmaintain spatial heterogeneity the influenceof scale on eco-logical interactionsandhowmanagementofspatialheterogeneityregulatesecologicalprocesses(Turner19892005)Amajorthemeinlandscapeecologyistheapplicationofhierarchytheorytodecou-ple complex systems into smaller components as ameans of sim-plifyingresearchofwholesystems(AllenampStarr2017Wu2013)Thisispossiblebecauseanecologicalsystemthatoperatesasatruehierarchycanbecharacterisedasa system of systems within systems (King 1997) For example foraging by herbivores occurswithin anestedhierarchy inwhich local feedingstationsarenestedwithinlarger plant community patches and patches are in turn nestedwithinbroader landscapeandregionalsystems(Senftetal1987)Theprinciplesoflandscapeecologyincludinghierarchytheoryareapplicable to stream ecosystems despite the implicit reference toland(Wiens2002)InfactFrissellLissWarrenandHurley(1986)andFauschTorgersenBaxterandLi (2002)describedthenestedhierarchy of stream habitats including microhabitats (10minus1 to 0m)nestedwithinchannelunitssuchaspoolsorriffles(101ndash2m)nestedwithin reaches (102ndash3m)nestedwithinsegments (103ndash5m)nestedwithinstreamsystems(otherwiseknownasbasins105ndash6m)Theseandother studies (LabbeampFausch2000)highlighted theprocessofviewingstreamnetworksasriverscapehierarchiestoinvestigatemultiscalevariablesthatregulateorganismabundanceanddistribu-tionRiverscapeperspectivesareincreasinglyappliedtochallengesfacing conservation of biodiversity in aquatic ecosystems (ErősOHanleyampCzegleacutedi2018Fausch2010)

Assessing the riverscapeecologyof fishes in theGreatPlainsUSA isofcriticalconservation interestbecausehabitatdiversityiscommonlysimplifiedbyanthropogeniclandscapealterationsop-eratingacrossmultiplescalesDroughtandfloodingarenaturalhy-drologicdisturbances intheGreatPlainsandcauseexpansionandcontractionof theheterogeneity and scaleof riverscapes (DoddsGidoWhiles Fritz ampMatthews 2004 Stanley Fisher ampGrimm1997)HoweveranthropogenicmodificationstoGreatPlainsriver-scapeshavedisruptednaturalpatternsinspatialheterogeneitywithnegativeconsequencesforecologicalprocesses involvingendemicfishes (Hoagstrom BrooksampDavenport 2011)Multi-scale alter-ationstoecologicalprocessesresultincompetitionwithnon-nativespeciesacrosslocalhabitats(GidoSchaeferampPigg2004LabbeampFausch2000)degradationofwaterqualityacrossreaches(Cross

1950) altered hydrologic regimes across segments (Costigan ampDaniels2012)andfragmentationofhydrologicconnectivity(PerkinampGido 2011Worthington BrewerGrabowskiampMueller 2014)and dewatering of streams and aquifers (Perkin Gido CostiganDanielsampJohnson2015PerkinGidoCooperetal2015Perkinetal 2017) across basins These multi-scale alterations requiremulti-scaleassessmentsofconservationstatusparticularlyforre-gionallyendemicArkansasdarterEtheostoma craigini(seeoverviewbyLabbeampFausch2000)InthestateofColoradoArkansasdarterconservationactionsnowconsiderpool-scalehabitatrefuge(SmithampFausch1997)reach-scalehabitatconnectivity(GroceBaileyampFausch2012)andsegment-scalepopulationstructure(FitzpatrickCrockett amp Funk 2014) Despite abundant research in ColoradoArkansasdarterhasdeclined locally throughoutmuchof its rangebecauseofchangestoGreatPlainsriverscapes(USFishandWildlifeService2016) suggestingadditional research isnecessary toplanconservationactionsinvolvingmulti-scaleenvironmentalregulatorsofArkansasdarterabundance

Empirical models describing relationships between Arkansasdarter abundance and habitat dimension and heterogeneity arenecessary to inform conservation actions Habitat dimension canbemeasuredasstreamwidth(m)anddepth(m)whereasheteroge-neityinvolvesstructuressuchasaquaticvegetationcanopycoverandinstreamwoodystructureEachofthesecomponentsofhabitatisregulatedbyhydrologicprocessesthatlinkstreamstoterrestriallandscapes (BurcherValettampBenfield2007PerkinTroiaShawGerkenampGido2016)Forexampleterrestrialhabitattransforma-tion has disrupted historic vegetative succession regimes and al-lowedforwoodyencroachmentacrossbasins (Briggsetal2005)andthisaffectsstreamreachesandsegmentsbystabilisingbanksincreasingstreamdepthsclosingotherwiseopencanopiesandde-positing instreamwoodystructure (Fischeretal2010Poffetal1997)Whetherornotandtowhatextent thesehabitatchangesaffectArkansasdarterabundancehasnotbeeninvestigated(EberleampErnsting2014)Furthermoreabundance-basedmodelsarecrit-ical because conservation and restoration goals are routinely setaround abundance data and descriptivemodels provide some ex-pectation for the benefits associated with specific conservationactionsDependingonthenatureofrelationshipshabitatscanbemanipulatedtobenefitfishabundancesthroughpracticessuchasri-pariantreeplantingsorremovalsatfinescalesaswellascoordinatedlandusepracticesacrossbroaderscales (KwakampFreeman2010)Simultaneousassessmentoftheappropriatehabitatdimensionsandheterogeneityacrossspatialscaleswillhighlighttheappropriateac-tionsandspatialextentsforimplementinghabitatpreservationand

appropriatespatialscalesandbenefitnativefishconservationbyhighlightingtheapplicationofhierarchytheorytoaddressmanagementchallenges

K E Y W O R D S

conservationbiologyfishecologylandscapeecologyscalingstreamsandrivers










2emsp |emspMETHODS
















3emsp |emspRESULTS





Reach

1+D+C+(1+D+C|SV) 16759 00 0999 054

1+D+WS+(1+D+WS|SV) 17250 491 lt0001 050

1+WS+C+(1+WS+C|SV) 19157 2398 lt0001 028

1+W+C+(1+W+C|SV) 19458 2699 lt0001 040

1+D+V+(1+D+V|SV) 20541 3782 lt0001 051

1+W+WS+(1+W+WS|SV) 20643 3884 lt0001 029

1+D+W+(1+D+W|SV) 20723 3964 lt0001 038

1+V+C+(1+V+C|SV) 20906 4147 lt0001 044

1+WS+V+(1+WS+V|SV) 21006 4247 lt0001 028

1+C+(1+C|SV) 21220 4461 lt0001 044

1+WS+(1+WS|SV) 21367 4608 lt0001 034

1+D+(1+D|SV) 22723 5964 lt0001 049

1+W+V+(1+W+V|SV) 23859 7100 lt0001 015

1+W+(1+W|SV) 25721 8962 lt0001 011

1+V+(1+V|SV) 26765 10006 lt0001 000

1+(1|SV) 27349 10590 lt0001 000

Segment

1+D+C+(1+D+C|SV) 3887 00 0999 056

1+D+W+(1+D+W|SV) 4022 135 lt0001 045

1+W+C+(1+W+C|SV) 4102 215 lt0001 064

1+W+WS+(1+W+WS|SV) 4483 596 lt0001 065

1+W+V+(1+W+V|SV) 4647 760 lt0001 062

1+D+V+(1+D+V|SV) 4702 815 lt0001 059

1+D+WS+(1+D+WS|SV) 4991 1104 lt0001 069

1+D+(1+D|SV) 5688 1802 lt0001 065

1+V+C+(1+V+C|SV) 6955 3068 lt0001 034

1+WS+C+(1+WS+C|SV) 7689 3802 lt0001 033

1+W+(1+W|SV) 8233 4347 lt0001 049

1+WS+V+(1+WS+V|SV) 8310 4423 lt0001 025

1+V+(1+V|SV) 8951 5065 lt0001 038

1+C+(1+C|SV) 9094 5207 lt0001 040

1+WS+(1+WS|SV) 9117 5230 lt0001 032

1+(1|SV) 11347 7460 lt0001 000

Basin

1+D+W+(1+D+W|SV) 253912 000 0999 037

1+W+WS+(1+W+WS|SV) 288152 34240 lt0001 013

1+WS+C+(1+WS+C|SV) 297048 43136 lt0001 000

1+W+V+(1+W+V|SV) 298539 44627 lt0001 009

1+W+C+(1+W+C|SV) 304779 50866 lt0001 020

1+W+(1+W|SV) 327651 73738 lt0001 040

1+D+C+(1+D+C|SV) 367322 113410 lt0001 002

1+V+C+(1+V+C|SV) 416767 162854 lt0001 006

(Continues)






1+D+V+(1+D+V|SV) 439163 185250 lt0001 001

1+C+(1+C|SV) 458019 204107 lt0001 002

1+D+WS+(1+D+WS|SV) 468114 214201 lt0001 000

1+WS+V+(1+WS+V|SV) 480510 226598 lt0001 004

1+D+(1+D|SV) 487642 233730 lt0001 000

1+V+(1+V|SV) 512335 258422 lt0001 002

1+WS+(1+WS|SV) 569878 315966 lt0001 004

1+(1|SV) 587230 333317 lt0001 000




















ACKNOWLEDG MENTS




R E FE R E N C E S























































































2emsp |emspMETHODS
















3emsp |emspRESULTS





Reach

1+D+C+(1+D+C|SV) 16759 00 0999 054

1+D+WS+(1+D+WS|SV) 17250 491 lt0001 050

1+WS+C+(1+WS+C|SV) 19157 2398 lt0001 028

1+W+C+(1+W+C|SV) 19458 2699 lt0001 040

1+D+V+(1+D+V|SV) 20541 3782 lt0001 051

1+W+WS+(1+W+WS|SV) 20643 3884 lt0001 029

1+D+W+(1+D+W|SV) 20723 3964 lt0001 038

1+V+C+(1+V+C|SV) 20906 4147 lt0001 044

1+WS+V+(1+WS+V|SV) 21006 4247 lt0001 028

1+C+(1+C|SV) 21220 4461 lt0001 044

1+WS+(1+WS|SV) 21367 4608 lt0001 034

1+D+(1+D|SV) 22723 5964 lt0001 049

1+W+V+(1+W+V|SV) 23859 7100 lt0001 015

1+W+(1+W|SV) 25721 8962 lt0001 011

1+V+(1+V|SV) 26765 10006 lt0001 000

1+(1|SV) 27349 10590 lt0001 000

Segment

1+D+C+(1+D+C|SV) 3887 00 0999 056

1+D+W+(1+D+W|SV) 4022 135 lt0001 045

1+W+C+(1+W+C|SV) 4102 215 lt0001 064

1+W+WS+(1+W+WS|SV) 4483 596 lt0001 065

1+W+V+(1+W+V|SV) 4647 760 lt0001 062

1+D+V+(1+D+V|SV) 4702 815 lt0001 059

1+D+WS+(1+D+WS|SV) 4991 1104 lt0001 069

1+D+(1+D|SV) 5688 1802 lt0001 065

1+V+C+(1+V+C|SV) 6955 3068 lt0001 034

1+WS+C+(1+WS+C|SV) 7689 3802 lt0001 033

1+W+(1+W|SV) 8233 4347 lt0001 049

1+WS+V+(1+WS+V|SV) 8310 4423 lt0001 025

1+V+(1+V|SV) 8951 5065 lt0001 038

1+C+(1+C|SV) 9094 5207 lt0001 040

1+WS+(1+WS|SV) 9117 5230 lt0001 032

1+(1|SV) 11347 7460 lt0001 000

Basin

1+D+W+(1+D+W|SV) 253912 000 0999 037

1+W+WS+(1+W+WS|SV) 288152 34240 lt0001 013

1+WS+C+(1+WS+C|SV) 297048 43136 lt0001 000

1+W+V+(1+W+V|SV) 298539 44627 lt0001 009

1+W+C+(1+W+C|SV) 304779 50866 lt0001 020

1+W+(1+W|SV) 327651 73738 lt0001 040

1+D+C+(1+D+C|SV) 367322 113410 lt0001 002

1+V+C+(1+V+C|SV) 416767 162854 lt0001 006

(Continues)






1+D+V+(1+D+V|SV) 439163 185250 lt0001 001

1+C+(1+C|SV) 458019 204107 lt0001 002

1+D+WS+(1+D+WS|SV) 468114 214201 lt0001 000

1+WS+V+(1+WS+V|SV) 480510 226598 lt0001 004

1+D+(1+D|SV) 487642 233730 lt0001 000

1+V+(1+V|SV) 512335 258422 lt0001 002

1+WS+(1+WS|SV) 569878 315966 lt0001 004

1+(1|SV) 587230 333317 lt0001 000




















ACKNOWLEDG MENTS




R E FE R E N C E S
















































































2emsp |emspMETHODS
















3emsp |emspRESULTS





Reach

1+D+C+(1+D+C|SV) 16759 00 0999 054

1+D+WS+(1+D+WS|SV) 17250 491 lt0001 050

1+WS+C+(1+WS+C|SV) 19157 2398 lt0001 028

1+W+C+(1+W+C|SV) 19458 2699 lt0001 040

1+D+V+(1+D+V|SV) 20541 3782 lt0001 051

1+W+WS+(1+W+WS|SV) 20643 3884 lt0001 029

1+D+W+(1+D+W|SV) 20723 3964 lt0001 038

1+V+C+(1+V+C|SV) 20906 4147 lt0001 044

1+WS+V+(1+WS+V|SV) 21006 4247 lt0001 028

1+C+(1+C|SV) 21220 4461 lt0001 044

1+WS+(1+WS|SV) 21367 4608 lt0001 034

1+D+(1+D|SV) 22723 5964 lt0001 049

1+W+V+(1+W+V|SV) 23859 7100 lt0001 015

1+W+(1+W|SV) 25721 8962 lt0001 011

1+V+(1+V|SV) 26765 10006 lt0001 000

1+(1|SV) 27349 10590 lt0001 000

Segment

1+D+C+(1+D+C|SV) 3887 00 0999 056

1+D+W+(1+D+W|SV) 4022 135 lt0001 045

1+W+C+(1+W+C|SV) 4102 215 lt0001 064

1+W+WS+(1+W+WS|SV) 4483 596 lt0001 065

1+W+V+(1+W+V|SV) 4647 760 lt0001 062

1+D+V+(1+D+V|SV) 4702 815 lt0001 059

1+D+WS+(1+D+WS|SV) 4991 1104 lt0001 069

1+D+(1+D|SV) 5688 1802 lt0001 065

1+V+C+(1+V+C|SV) 6955 3068 lt0001 034

1+WS+C+(1+WS+C|SV) 7689 3802 lt0001 033

1+W+(1+W|SV) 8233 4347 lt0001 049

1+WS+V+(1+WS+V|SV) 8310 4423 lt0001 025

1+V+(1+V|SV) 8951 5065 lt0001 038

1+C+(1+C|SV) 9094 5207 lt0001 040

1+WS+(1+WS|SV) 9117 5230 lt0001 032

1+(1|SV) 11347 7460 lt0001 000

Basin

1+D+W+(1+D+W|SV) 253912 000 0999 037

1+W+WS+(1+W+WS|SV) 288152 34240 lt0001 013

1+WS+C+(1+WS+C|SV) 297048 43136 lt0001 000

1+W+V+(1+W+V|SV) 298539 44627 lt0001 009

1+W+C+(1+W+C|SV) 304779 50866 lt0001 020

1+W+(1+W|SV) 327651 73738 lt0001 040

1+D+C+(1+D+C|SV) 367322 113410 lt0001 002

1+V+C+(1+V+C|SV) 416767 162854 lt0001 006

(Continues)






1+D+V+(1+D+V|SV) 439163 185250 lt0001 001

1+C+(1+C|SV) 458019 204107 lt0001 002

1+D+WS+(1+D+WS|SV) 468114 214201 lt0001 000

1+WS+V+(1+WS+V|SV) 480510 226598 lt0001 004

1+D+(1+D|SV) 487642 233730 lt0001 000

1+V+(1+V|SV) 512335 258422 lt0001 002

1+WS+(1+WS|SV) 569878 315966 lt0001 004

1+(1|SV) 587230 333317 lt0001 000




















ACKNOWLEDG MENTS




R E FE R E N C E S





















































































3emsp |emspRESULTS





Reach

1+D+C+(1+D+C|SV) 16759 00 0999 054

1+D+WS+(1+D+WS|SV) 17250 491 lt0001 050

1+WS+C+(1+WS+C|SV) 19157 2398 lt0001 028

1+W+C+(1+W+C|SV) 19458 2699 lt0001 040

1+D+V+(1+D+V|SV) 20541 3782 lt0001 051

1+W+WS+(1+W+WS|SV) 20643 3884 lt0001 029

1+D+W+(1+D+W|SV) 20723 3964 lt0001 038

1+V+C+(1+V+C|SV) 20906 4147 lt0001 044

1+WS+V+(1+WS+V|SV) 21006 4247 lt0001 028

1+C+(1+C|SV) 21220 4461 lt0001 044

1+WS+(1+WS|SV) 21367 4608 lt0001 034

1+D+(1+D|SV) 22723 5964 lt0001 049

1+W+V+(1+W+V|SV) 23859 7100 lt0001 015

1+W+(1+W|SV) 25721 8962 lt0001 011

1+V+(1+V|SV) 26765 10006 lt0001 000

1+(1|SV) 27349 10590 lt0001 000

Segment

1+D+C+(1+D+C|SV) 3887 00 0999 056

1+D+W+(1+D+W|SV) 4022 135 lt0001 045

1+W+C+(1+W+C|SV) 4102 215 lt0001 064

1+W+WS+(1+W+WS|SV) 4483 596 lt0001 065

1+W+V+(1+W+V|SV) 4647 760 lt0001 062

1+D+V+(1+D+V|SV) 4702 815 lt0001 059

1+D+WS+(1+D+WS|SV) 4991 1104 lt0001 069

1+D+(1+D|SV) 5688 1802 lt0001 065

1+V+C+(1+V+C|SV) 6955 3068 lt0001 034

1+WS+C+(1+WS+C|SV) 7689 3802 lt0001 033

1+W+(1+W|SV) 8233 4347 lt0001 049

1+WS+V+(1+WS+V|SV) 8310 4423 lt0001 025

1+V+(1+V|SV) 8951 5065 lt0001 038

1+C+(1+C|SV) 9094 5207 lt0001 040

1+WS+(1+WS|SV) 9117 5230 lt0001 032

1+(1|SV) 11347 7460 lt0001 000

Basin

1+D+W+(1+D+W|SV) 253912 000 0999 037

1+W+WS+(1+W+WS|SV) 288152 34240 lt0001 013

1+WS+C+(1+WS+C|SV) 297048 43136 lt0001 000

1+W+V+(1+W+V|SV) 298539 44627 lt0001 009

1+W+C+(1+W+C|SV) 304779 50866 lt0001 020

1+W+(1+W|SV) 327651 73738 lt0001 040

1+D+C+(1+D+C|SV) 367322 113410 lt0001 002

1+V+C+(1+V+C|SV) 416767 162854 lt0001 006

(Continues)






1+D+V+(1+D+V|SV) 439163 185250 lt0001 001

1+C+(1+C|SV) 458019 204107 lt0001 002

1+D+WS+(1+D+WS|SV) 468114 214201 lt0001 000

1+WS+V+(1+WS+V|SV) 480510 226598 lt0001 004

1+D+(1+D|SV) 487642 233730 lt0001 000

1+V+(1+V|SV) 512335 258422 lt0001 002

1+WS+(1+WS|SV) 569878 315966 lt0001 004

1+(1|SV) 587230 333317 lt0001 000




















ACKNOWLEDG MENTS




R E FE R E N C E S

















































































Reach

1+D+C+(1+D+C|SV) 16759 00 0999 054

1+D+WS+(1+D+WS|SV) 17250 491 lt0001 050

1+WS+C+(1+WS+C|SV) 19157 2398 lt0001 028

1+W+C+(1+W+C|SV) 19458 2699 lt0001 040

1+D+V+(1+D+V|SV) 20541 3782 lt0001 051

1+W+WS+(1+W+WS|SV) 20643 3884 lt0001 029

1+D+W+(1+D+W|SV) 20723 3964 lt0001 038

1+V+C+(1+V+C|SV) 20906 4147 lt0001 044

1+WS+V+(1+WS+V|SV) 21006 4247 lt0001 028

1+C+(1+C|SV) 21220 4461 lt0001 044

1+WS+(1+WS|SV) 21367 4608 lt0001 034

1+D+(1+D|SV) 22723 5964 lt0001 049

1+W+V+(1+W+V|SV) 23859 7100 lt0001 015

1+W+(1+W|SV) 25721 8962 lt0001 011

1+V+(1+V|SV) 26765 10006 lt0001 000

1+(1|SV) 27349 10590 lt0001 000

Segment

1+D+C+(1+D+C|SV) 3887 00 0999 056

1+D+W+(1+D+W|SV) 4022 135 lt0001 045

1+W+C+(1+W+C|SV) 4102 215 lt0001 064

1+W+WS+(1+W+WS|SV) 4483 596 lt0001 065

1+W+V+(1+W+V|SV) 4647 760 lt0001 062

1+D+V+(1+D+V|SV) 4702 815 lt0001 059

1+D+WS+(1+D+WS|SV) 4991 1104 lt0001 069

1+D+(1+D|SV) 5688 1802 lt0001 065

1+V+C+(1+V+C|SV) 6955 3068 lt0001 034

1+WS+C+(1+WS+C|SV) 7689 3802 lt0001 033

1+W+(1+W|SV) 8233 4347 lt0001 049

1+WS+V+(1+WS+V|SV) 8310 4423 lt0001 025

1+V+(1+V|SV) 8951 5065 lt0001 038

1+C+(1+C|SV) 9094 5207 lt0001 040

1+WS+(1+WS|SV) 9117 5230 lt0001 032

1+(1|SV) 11347 7460 lt0001 000

Basin

1+D+W+(1+D+W|SV) 253912 000 0999 037

1+W+WS+(1+W+WS|SV) 288152 34240 lt0001 013

1+WS+C+(1+WS+C|SV) 297048 43136 lt0001 000

1+W+V+(1+W+V|SV) 298539 44627 lt0001 009

1+W+C+(1+W+C|SV) 304779 50866 lt0001 020

1+W+(1+W|SV) 327651 73738 lt0001 040

1+D+C+(1+D+C|SV) 367322 113410 lt0001 002

1+V+C+(1+V+C|SV) 416767 162854 lt0001 006

(Continues)






1+D+V+(1+D+V|SV) 439163 185250 lt0001 001

1+C+(1+C|SV) 458019 204107 lt0001 002

1+D+WS+(1+D+WS|SV) 468114 214201 lt0001 000

1+WS+V+(1+WS+V|SV) 480510 226598 lt0001 004

1+D+(1+D|SV) 487642 233730 lt0001 000

1+V+(1+V|SV) 512335 258422 lt0001 002

1+WS+(1+WS|SV) 569878 315966 lt0001 004

1+(1|SV) 587230 333317 lt0001 000




















ACKNOWLEDG MENTS




R E FE R E N C E S



















































































1+D+V+(1+D+V|SV) 439163 185250 lt0001 001

1+C+(1+C|SV) 458019 204107 lt0001 002

1+D+WS+(1+D+WS|SV) 468114 214201 lt0001 000

1+WS+V+(1+WS+V|SV) 480510 226598 lt0001 004

1+D+(1+D|SV) 487642 233730 lt0001 000

1+V+(1+V|SV) 512335 258422 lt0001 002

1+WS+(1+WS|SV) 569878 315966 lt0001 004

1+(1|SV) 587230 333317 lt0001 000




















ACKNOWLEDG MENTS




R E FE R E N C E S






























































































ACKNOWLEDG MENTS




R E FE R E N C E S























































































ACKNOWLEDG MENTS




R E FE R E N C E S


















































































ACKNOWLEDG MENTS




R E FE R E N C E S




























































































































































































Documents

Hierarchy theory reveals multiscale predictors of Arkansas ......River basin, a tributary of the Arkansas River in southcentral Kansas, U.S.A. (Figure 1). Average annual precipitation