J Appl Ecol. 2017;1–10. wileyonlinelibrary.com/journal/jpe  | 1© 2017 The Authors. Journal of Applied Ecology © 2017 British Ecological Society

Received:27February2017  |  Accepted:11September2017DOI: 10.1111/1365-2664.13013

R E S E A R C H A R T I C L E

Large woody debris “rewilding” rapidly restores biodiversity in riverine food webs

Murray S. A. Thompson1,2,3  | Stephen J. Brooks1 | Carl D. Sayer2 | Guy Woodward4 |  Jan C. Axmacher2 | Daniel M. Perkins5 | Clare Gray4

1DepartmentofLifeSciences,NaturalHistoryMuseum,London,UK2EnvironmentalChangeResearchCentre(ECRC),DepartmentofGeography,UniversityCollegeLondon,London,UK3CentreforEnvironment,FisheriesandAquacultureScience,LowestoftLaboratory,Suffolk,UK4DepartmentofLifeSciences,ImperialCollegeLondon,Ascot,Berkshire,UK5DepartmentofLifeSciences,WhitelandsCollege,UniversityofRoehampton,London,UK

CorrespondenceMurrayS.A.ThompsonEmail:murray.thompson@cefas.co.uk

HandlingEditor:Marie-JoséeFortin

Abstract1. Extensive habitat destruction and pollution have caused dramatic declines inaquaticbiodiversityat localtoglobalscales. Inrivers,thereintroductionof largewoody debris is a common method aimed at restoring degraded ecosystemsthrough“rewilding.”However,causalevidenceforitseffectivenessislackingduetoadearthofreplicatedbefore–aftercontrol-impactfieldexperiments.

2. We conducted the first replicated experiment of large woody debris rewildingacrossmultipleriversandorganisationallevels,fromindividualtargetspeciespopu-lationstoentirefoodwebs.

3. Forthefirsttime,wedemonstratecausallinksbetweenhabitatrestoration,biodi-versityrestorationandfoodwebresponses.Populationsof invertebratesandanapexpredator,browntrout (Salmo trutta), increased,andfoodwebanalysissug-gested increasedbiomass flux frombasal resources to invertebrates and subse-quentlyfisheswithinrestoredreaches.

4. Synthesis and applications.Thisstudycontributessignificantnewevidencedemon-strating that largewoody debris rewilding can help to restore human-impactedriverecosystems,primarily throughaltering theabundanceandbiomassof con-sumersandresourcesinthefoodweb.Wealsooutlineameanstogaugethemag-nitudeofecologicalresponsestorestoration,relativetoenvironmentalstressors,whichcouldhelptoprioritisethemosteffectiveconservationefforts.

K E Y W O R D S

BACI,biodiversity,biomonitoring,fieldexperiment,foodwebs,rewilding,riverrestoration,riversystems,trivariateanalysis,woodydebris

1  | INTRODUCTION

Overexploitation, pollution and habitat destruction are causingglobaldeclinesinfreshwaterbiodiversity(Strayer&Dudgeon,2010;Vörösmarty etal., 2010), especially in running waters (Nilsson,Reidy, Dynesius, & Revenga, 2005; Stein & Kutner, 2000). Despitewidespread improvements inwater quality in the developedworld,ecologicalrecoveryinrivershasoftenbeenpatchy,sloworevenen-tirely lacking (Battarbee,Shilland,Kernan,Monteith,&Curtis,2014;

Langford,Shaw,Ferguson,&Howard,2009).Thissuggeststhatenvi-ronmentaldrivers,whichwerepreviouslysubordinatetopoorwaterquality,arenowactingasprincipalbottleneckswherechemicalcon-ditionshaveimproved.Foremostamongtheseishabitatdegradationassociatedwithriverstraightening,channelisation,impoundmentandclearanceoflargewoodydebris(alsotermedlargewood,henceforthLW),which has beenongoing around theworld formany centuries(Downs&Gregory,2014).Thesemodifications restrictnatural riverdynamics, such as LW processes that determine the frequency of

2  |    Journal of Applied Ecology THOMPSON eT al.

poolsand riffles,withoftendeleterious implications forecosystems(Brooker,1985;Gurnell&Sweet,1998).

Largewoodhasbeenused toenhance in-riverhabitat through-out the world for over a century in tens of thousands of projects(Bernhardtetal.,2005;Feldetal.,2011;Roni,Beechie,Pess,Hanson,&Jonsson,2015).Inrecenttimes,“rewilding”approaches,suchasre-introducingbeaversor fellingwhole trees into the river to replicatenaturaltreefall,havebeen increasinglyusedasameanstoreinstatenatural processes, restore biodiversity and thus recover degradedriver ecosystems (Baker & Eckerberg, 2016; Hood& Larson, 2015;Roni&Beechie,2012).LW-basedhabitatrestorationhasbeenlinkedtoincreasesinfishandinvertebratepopulations(Kail,Hering,Muhar,Gerhard, & Preis, 2007; Roni etal., 2015; Schneider &Winemiller,2008), increases in allochthonous and autochthonous resources forinvertebrates(Cashman,Pilotto,&Harvey,2016;Gurnell,Gregory,&Petts, 1995), and increased provision of refugia for organisms fromhigh flows (Borchardt, 1993) and predation (Everett & Ruiz, 1993).However, the assumedbiodiversity enhancement following the res-torationof habitat diversity is strongly contested in the absenceofunequivocal evidence (Feld etal., 2011; Lepori, Palm, Brännäs, &Malmqvist, 2005; Palmer, Menninger, & Bernhardt, 2010; but seeKail, Brabec, Poppe,&Januschke, 2015; Pilotto, Bertoncin,Harvey,Wharton,&Pusch,2014).

Due to a lack of replication and standardisation of monitoringtechniques, thesuitabilityofproxies (e.g. riverhabitatqualityortheabundanceofkeytaxa)assurrogates foreffectiveecosystemresto-rationremainsunverified(Bernhardt&Palmer,2011;Feldetal.,2011;Palmer etal., 2010).Where biomonitoring has been undertaken toassessrestorationsuccess,invertebratesorfishhaveoftenbeenthesole bioindicators used (Matthews, Reeze, Feld, & Hendriks, 2010;Whiteway,Biron,Zimmermann,Venter,&Grant,2010;but seeKailetal., 2015).Despite being repeatedly advocated (Feld etal., 2011;Fribergetal.,2011;Pander&Geist,2013),amoreholistic, system-based view of restoration responses at higher levels of biologicalorganisationisstill lacking.Furthermore,nostudytoourknowledgehas compared both control (i.e. unrestored) and target conditions(i.e.thosenaturallycreatedwhichtheinterventionaimstoreplicate)acrossriversinamultiplebefore–aftercontrol-impact(MBACI;sensuDownesetal.,2002)framework.Thisisnonethelesstheonlywaytoisolate potentially confounding drivers of ecological change in bothspaceandtimetotestwhetherecosystemsareconsistentlyrestoredtotargetconditions.

Weaddressthisknowledgegapbycomparingecologicalpatternsbetweencontrolreaches(i.e.thosewithnoLW),reacheswithnatu-rallyfallenLWpriortorestoration(i.e.“target”),andthosecontainingfelledLW(i.e.“restored”)inaMBACIexperiment.ThiswasconductedacrossfiveBritishlowlandriversthathavebeensubjectedtoriverhab-itatdegradationandpollutiontypicalforsuchsystems(EnvironmentAgencyEnglish Nature, 2004; WWF-UK, 2015). Recent studies(Heringetal.,2015;Kailetal.,2015)suggestthatriverrestorationcanaffectbiotaquickly,theeffectsofrestorationcandiminishovertime,andthatrestorationscaleisaweakdeterminantofrestorationeffect.Thus,bycomparingcontrol,targetandrestoredreaches,ouraimwas

toassessshort-term(<1yearpost-restoration)responsesto individ-ualLWstructures,whilealsogivingalonger-termperspectiveonthetrajectoryofecologicalrecovery,asrestoredreachesdevelopfromadegradedtoamorefullyrestored“target”state.Suchanapproachisvital inafieldwheremonitoringresourcesare limitedandextendedtemporalsampling(>2years)israrelyfeasible(Feldetal.,2011).

Tounderstandreach-scaleeffectsof restorationonthecommu-nity,weinvestigatedchangesinthemassandabundanceofspeciespopulationsandthelinksbetweenthem(trophicinteractions)infoodwebs using “trivariate analyses” (sensuCohen, Schittler, Raffaelli, &Reuman,2009),aswellastheirmoretraditionalunivariateandbivar-iate componentmeasures (e.g. linkagedensityandmass-abundancescaling exponents, respectively). Because invertebrate assemblagesrespondtohabitatchange(Demars,Kemp,Friberg,Usseglio-Polatera,&Harper,2012),formtheintermediatenodesinaquaticfoodwebs,and are widely used as bioindicators in habitat restoration stud-ies (Matthews etal., 2010; Palmer etal., 2010), we investigatedassemblage-levelresponsetoLWrestorationacrossreachesandbe-tweenlocalhabitatpatches.Wetestedthefollowinghypotheses:(1)LWrestorationaffectsmultiplelevelsofbiologicalorganisation,fromspecies’populationstoentirefoodwebs:specieswithmanypredatorsand thoseespecially sensitive todeterioratingenvironmental condi-tionswillprosperfromtheincreasedrefugiaandrestoredconditionsprovidedbyLW;anincreaseinspeciesrichnesswillresultinincreasesinboth feeding-linkdiversityandnewfeedingpathways in restoredfoodwebs; (2)foodwebs intherecentlyrestoredreachesare inter-mediatebetweencontrolandtargetconditionsassmall,vagile,fast-growing species (e.g. invertebrates) respond to elevated resources(i.e.refugiaandavailableenergy)beforelarge,long-livedspecies(e.g.fish); (3) LW restoration increases invertebrate species richness (i.e.α-diversity)atthereach-scaleandenhancesinvertebratecommunitydissimilarity(i.e.β-diversity)withinreachesashabitat-specificassem-blages colonise LW.Where frequently used control-impact designscannotestablishcausationandstandardBACIdesignsareunabletoreveal theconsistencyof recoverypatterns, theMBACIapproach isperfectlysuitedtoaddressthesehypotheses.

2  | MATERIALS AND METHODS

2.1 | Study sites, restoration and experimental design

WesampledfiveUKlowlandchalkrivers(Figure1;TableS1)thatspana range of nutrient concentrations representative of such systems(i.e.ortho-phosphateconcentrationsof37.7–308.5μgl−1represent-ingrelativelylowtomoderatelyenrichedwaters;UKTAG,2013).Oneachriver,wesurveyedan“impact”reach,designatedforrestoration,andanunrestored“control”reach,whichresembledthechannelformandripariansurroundingsthatexistedinthe(pre) impactreach.Wealsosurveyeda“target”reachwherenaturallyfallentreeshadbeeninplacefor3–5yearspriortorestorationonfouroftherivers.TherewerenoavailabletargetconditionsattheR.Wensum,however.Thismeantwehadtwotemporalcontrolsatfourofourrivers(i.e.control

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andtargetreaches),whichisconsideredanimportant,butoftenover-looked,requirementinBACIdesigns(Underwood,1994).

Reacheswere25m in length,100–500mapart ineach river tomaintain independence, and ordered randomly to avoid potentiallyconfounding longitudinaleffects (Harrisonetal.,2004).RestorationswereundertakeninlateOctoberandearlyNovember2010.Ineachriverwereplicated,ascloselyaspossible,theLWstructurefoundintargetconditions,thatis,byfellingthesamesizeandspeciesoftree,whichwere eitherwholeAlder (Alnus glutinosa L.) orWhiteWillow(Salix albaL.)atleast7mtallandof0.3mdiameteratthebaseofthetrunk.Felledtreesweretetheredtostakesfashionedfromtheirownbranches.

2.2 | Sampling protocol

Acrossallreaches,biological,physicalandchemicalsurveyswereun-dertakeninspring(mid-Marchtomid-April)2010beforerestorationandduringthesameperiodin2011followingrestoration.Estimatesweremade of the conditions and extent of LW, river-edge (i.e. upto1mfromthebank)andmid-riverhabitatsacrossagridoffifteen1 m2 quadrats divided between five equally spaced transects perreach (FigureS1).Usingabathyscope,proportionsof silt, sandandgravelsubstratewereestimatedvisuallytothenearest5%,andcoarsewoodydebris(<10cmdiameter),LW(>10cmdiameter)andplantoc-cupancyweremeasuredusingthe“percentagevolumeinfested”(PVI)system(Canfieldetal.,1984).Watervelocity(mS−1)wasmeasuredat60%depthusingaValeportBFM002flowmeterateachsurveypoint.Physicalriverreachcharacteristics(e.g.riverwidth,altitude,gradient)were collated alongside annual averages ofwater temperature and

chemistry (e.g. ortho-phosphate, total oxidised nitrogen, dissolvedoxygen,pHandalkalinity)collectedbytheUKEnvironmentAgency.

2.3 | Population abundance, community structure and trophic interactions

Epilithicbiofilmwassampledfromeightcobblesselectedhaphazardlyateachreach.EachcobblewasphotographedanditsuppersurfaceareacalculatedusingImage-Jsoftware(version1.42)toprovidedataperunitarea.Threecobbleswerescrapedonsite,preservedinLugol’siodine and prepared for diatom identification following Battarbee,Jones,Flower,andCameron(2001).Thefirst100diatomvalvesen-counteredwithina100-μmwidetransectcrossingthecentreofeachcoverslipwere identified tospecies, resulting in300valve identifi-cations per reach that is considered optimal for determining com-munity composition (Besse-Lototskaya, Verdonschot, & Sinkeldam,2006).Fulldetailsofdiatomabundanceanddrymassestimationaregiven inSupportingMaterialsandMethods (seealsoTableS2).Theremainingfivecobbleswerestoredinthedarkat−20°C.Biofilmwasremoved from theupper surfaceofeach stoneusinga toothbrush.Chlorophyll-a (a proxy for algal biomass) was cold-extracted using90%acetoneand itsconcentrationdeterminedusingaspectropho-tometer(Ritchie,2006).

Invertebratesweresampledfromedge,midandLWhabitats inordertoassessrestorationeffectswithinreach,aswellasbetweenreaches (Figure S1).We used these habitat types as the samplingunitbecausethisallowedafullyreplicatedstratifieddesignacrossreaches and years.AHess sampler (0.017m2)with 335-μmmeshwas used to collect invertebrates and coarse (CPOM) and fine

F IGURE  1 LocationsofriversusedinthisstudyintheUnitedKingdom.Upperandrightpanelshowscontrol(C),impact(I)andtarget(T)reacharrangementineachriverinrelationtodirectionofflow(indicatedbyarrows).TherewerenosuitabletargetreachesneartherestorationontheRiverWensum

Loddon

Lyde

WensumBure

Test

500 m0 km 100 N

Woodgate Carrat

TC I

Great Wood

T C I

Long Copse Cottage

TCI

DeanlandsFarm

Leckford Estate T

C I

C

I

Turf Common

Bure Loddon Lyde

Test

Wensum

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particulateorganicmatter(FPOM).TheHesssamplerhadarowofteethonthebaseinordertocutthroughbranches,andthussam-pleLWhabitatandtheunderlyingbenthos,inacomparablewaytoedge andmid habitats. Sampling followed a random stratified de-sign in each reach: five sampleswere collected frommid-channel(thelargesthabitatbyareaandthusexpectedtohavehighesthet-erogeneity),threefromchanneledge,andthreefromLW(n=263).Sampleswerepreservedin70%industrialmethylatedspirits.CPOMandFPOM,retainedon1mmand335μmsieves,respectively,weredetermined by weighing oven dried (80°C) organic material fromeachHesssample.Invertebrateswereidentifiedtothehighestpos-sibletaxonomicresolution(usuallyspecies)andcountedtoprovidedata per unit area. Organism body size spanned many orders-of-magnitudeinthecommunitiesstudiedhere(i.e.fromdiatomstofish,3.93×10−8to9.88×105mg,respectively), thuswedeemedriver-specific estimates of invertebrate taxonmeanbody size sufficientto assess community-level responses. Measurements were madeusingall invertebratescollected fromthecontrol reaches in2011,supplementedwithspecimensofraretaxafromotherreaches.Alistof regression equations used to determine individual invertebratedrymassesfromlineardimensions(e.g.head-capsulewidthsorbodylengths)isprovidedinTableS3.

Quantitativedepletionelectrofishingwasundertakenatthereach-level, andall fishcapturedwere identified to speciesandmeasuredto fork length.Abundance (individuals perm2)was estimated usingiterativemaximumweightedlikelihoodstatistics(Carle&Strub,1978).Dry-massestimatesweremadeforeachspeciesusinglength-massre-gressionequationsandwet-to-drymassconversions(Thompsonetal.,2016).AlargeHesssampler(0.14m2)wasusedattheWensumimpactreachduetotherelativelylowsamplingefficiencyofbullhead(Cottus gobioL.),ascatchesdidnotreduceonconsecutiverunsduringelec-trofishing(Lauridsenetal.,2012).Thisapproachwasnotnecessaryfortheotherreacheswherebullheaddensitiesweresuccessfullydepletedbyelectrofishing.Fulldetailsoffishabundanceanddrymassestima-tioncanbefoundinSupportingMaterialsandMethods.

At least three randomly selected fish gut-content samplesweretaken from individuals of each species from each reach (i.e. up tonineperriver)inbothyearswherenumberspermitted(n=132).Gutcontentswereidentifiedtothehighestpossibletaxonomiclevel(usu-ally species).As gut content analysis captures only a snapshot of apredator’s diet,wepooled all observed feeding links and combinedthesewithfeeding linkspublished inthe literatureand inarecentlycollateddatabaseof trophic interactionsfromUKfreshwaters (Grayetal.,2015).Weassumedthat ifa trophic interactionbetweentwospecieswasdirectlyobservedorreportedintheliterature,andthosesamespecieswerepresentwithinareach,thenthattrophicinterac-tionalsooccurred.Thisapproachhasbeenwidelyapplied(e.g.Mulder&Elser, 2009;Pocock, Evans,&Memmott, 2012; Strong&Leroux,2014), especially in theconstructionof river foodwebs (Grayetal.,2015; Layer,Hildrew,&Woodward, 2013; Layer, Riede,Hildrew,&Woodward,2010;Thompsonetal.,2016).Thepercentageofdirectlyobservedlinksthatwerealsoreportedintheliteraturewas99%:i.e.,only1%of the4,535observations fromgutcontentsanalysiswere

newrecords.FurtherdetailsoffoodwebconstructioncanbefoundinThompson etal. (2016) andGray etal. (2015),with feeding linksobservedhereforthefirsttimepresentedinTableS4.

2.4 | Food web analysis

Considering that species rare for their size (i.e. thosewithnegativeresiduals fromthegeneralmass-abundancescalingrelationshipthatspansthefoodwebinFigure2a)havebeenshowntobesensitivetodeterioratingenvironmentalconditions (Woodwardetal.,2012),weexpectedincreasesinthesespeciesasenvironmentalstressorswererelieved following restoration (Figure2b). In addition, species withmanypredators(i.e.thosewithelevated“vulnerability”)wereexpectedtoprosperfromtheincreasedrefugiaprovidedbyLW.Feeding-linkdiversitywasmeasuredusingchangesinthenumberoflinks,linkagedensity (i.e. the number of links divided by the number of species)

F IGURE  2 Hypotheticalaquatictrivariatefoodwebsondouble-Log10axes.Nodesrepresentmeanbodymass(M)andnumericalabundance (N)ofindividualtaxa;greysquares=rare-for-sizeinvertebratetaxa,blacksquares=taxafoundonlyinrestoredandtargetfoodwebs,solidblackline=newfeeding-link.(a)Controlorimpact-beforereach;(b)followinghabitatrestorationinvertebrateN and/or Mincreases,especiallytaxararefortheirsize,andthosewithmanypredatorsprosperingfromincreasedrefugiaprovidedbyLW;(c)targetreachesfollowinglonger-termrecoveryoffish

Log 10

(N)

Diatoms

Invertebrates

Lower-links

Upper-links

General regressionslope

Fish

Log10(M)

(a)

(b)

(c)

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andconnectance(i.e.theproportionofrealisedlinks;Martinez,1991).Increasesinconsumernodes,linksbetweenconsumersandincreasedpredatorgenerality (e.g. in theproportionof resource links toeachfishnode;sensuSchoener,1989)wereusedtoassessthepotentialfornetwork “rewiring” via alternative feedingpathways.We testedwhethersmall,vagile,fast-growinginvertebratetaxarespondedfasterthan large long-lived fish taxa by comparing food webs in the re-storedreacheswiththoseintargetreaches(seeFigure2b,c).Changesin feeding “link angles” (sensuCohen etal., 2009; Thompson etal.,2016)andbiomassstocks(e.g.fishbiomassperreach)wereusedtotestwhether the inferredbiomass flux increased following restora-tion,andwhetherthisresultedinincreasesinconsumerandpredatorbiomass (i.e.bottom-upeffects and/or release from top-downcon-trol).Wheretherewereincreasesinspeciesrichnesswhichmayhavemaskedchangesinlinkanglesacrossacommoncoreofspecies(e.g.treatmentlevelincreasesinrare-for-sizetaxawithmorenegativelinkanglescouldbiasresults),were-rantheanalysisafterremovinglinksuniquetoagivenreach.Allfoodwebstatisticswerecalculatedinr usingCheddar(Hudsonetal.,2012).

2.5 | Data analysis

Weusedprincipalcomponentsanalysisandnon-metricmultidimen-sionalscaling(NMDS)toordinatetheenvironmentalandinvertebratedata,respectively.Duetothenestedandunbalanceddesign,dataformultivariateanalysesweresplitintofoursubsets:(1)temporalvaria-tion,unrelatedtotherestoration,wasassessedusingcontrol-beforeandcontrol-afterdata;and(2)spatialvariation,unrelatedtotheresto-ration,wasassessedusingcontrol-beforeandimpact-beforedata;(3)control-afterandimpact-afterdatawereusedtotestforrestorationeffects;and(4) impact-afterandtarget-afterdatawereusedtotestfordifferencesbetweenrestoredandtargetconditions.WeusedanNMDSofthechord-normalisedexpectedspeciessharedindexofdis-similarity(CNESS,calculatedinCOMPAH96;Gallagher,1999)onthelargestcommonsamplesizetoprovideameasureofβ-diversitynotconfounded by the number of individuals encountered (Trueblood,Gallagher,&Gould,1994;Legendre&Gallagher,2001).Permutationtests(n=999)werethenusedtoevaluatethesignificanceofobserveddifferences between rivers, reach- and habitat-types. All multivari-ateanalyseswereperformedinrusingvegan(Oksanenetal.,2015).Estimatesofα-diversity(i.e.HillnumberqD,whereq =0)weremadein rusingiNEXT(Hsieh,Ma,&Chao,2014).BysettingabasesamplesizeandusingrarefactionbasedonHillnumbers,thisapproachrepre-sentsarobustwayofcomparingspeciesrichnesswheresamplesizesdiffer(Chaoetal.,2014).Taxathatwerenotresolvedtospecies,andwhichcouldthereforerepresentmultiplespecies,wereremovedfromanalysesofα- and β-diversity.

Generallinearmixedeffectmodels(GLMM;simulatingbinomialorPoissondistributedresponses),linearmixedeffectmodels(LMM;modelling normally distributed responses) and linearmodels (LM;modelling normally distributed response without random terms)were used to test for ecological responses, besides invertebratedissimilarity,toenvironmentaldrivers.Strictlypositive,non-integer

data (e.g. biomass)were Log10 transformed,with x+1when dataincludedvalues<1.Allmixedeffectmodelswereconstructed inr usinglme4(Bates,Maechler,Bolker,&Walker,2015).TargetedtestsfordifferencesbetweengroupmeanswerecarriedoutusingTukey’sall-pairwisecomparisonsthatcorrectsformultiplecomparisonsinr usingmultcomp (Hothorn,Bretz,&Westfall,2008).Habitatcondi-tionsincontrolreachesweresignificantlydifferentbetweenrivers(seeSupportingResults;FigureS2a).Thus,toaccountforbetween-river differences, river identitywas fitted as a random term in allinitialmodels and restored and target reacheswere compared tounrestored (control and before-impact) reaches to test for resto-rationeffects.Toassessthespatialscaleoftherestorationeffectoninvertebrates,andtodisentanglepotentiallyconfoundingvariables,thosemodelsincludedtheadditionalfixedtermsofhabitat-type(i.e.edge,midandLW), resource (i.e. algaeanddetritus) andpredator(i.e. fish) biomass. Where there was evidence of over-dispersionin GLMM (i.e. where residual deviance was substantially greaterthantheresidualdegreesof freedom),eachdatumrowwas fittedasanadditionalrandomterm(Bolker,2008).Onlysignificantvari-ableswere retained in the finalmodels (Table S5), as determinedusing the likelihood-ratio test onnestedmodels comparedwith aχ²distribution.

3  | RESULTS

3.1 | Responses across multiple levels of biological organisation

FollowingLWrestoration,whichsuccessfullyreplicatedtargetenvi-ronmentalconditions(seeSupportingResults,TableS6),therewasanincrease innodes (species) in restoredreach foodwebsonlywithinthe invertebrate assemblages (Table1; Table S7). These “new” taxafound in the restored reaches, but not in their respective controls,were rare for their size (i.e. they hadmore negative residuals fromthegeneral regression slopewhen comparedwith taxa common toall reaches;LM,F1519=118.1,p<.001;Figure3),andtherewasnodifferenceinthisresponsebetweenrestoredandtargetreaches(LM,F1=0.213,p=.64).Higherinvertebratevulnerabilityandfishgener-ality revealed that “new” invertebrate taxa alsohadmanypotentialpredators,andtheirpresenceintherestoredandtargetreacheswaslinkedtoanincreaseinbothintermediatelinksbetweeninvertebratesand thediversityof feeding interactions (i.e. linkagedensity)withinthosefoodwebs(Table1).

The abundance, but not biomass, of Salmo trutta increasedin restored and target reaches by 186% and 127%, respectively,comparedwithcontrolreaches(Table1).Increasesininvertebrateabundance and biomasswere restricted to LWhabitat, irrespec-tiveofreachtype(TableS5),indicatingthattherestorationeffectwaslocalised,andthatincreasesweresimilarinmagnitudeinboth,restoredandtargetreaches.Invertebrateabundanceacrossreachtypeswas102% (GLMM; z = 5.22; p<.001) and185% (z=7.28;p<.001; Figure S5f) higher in LWvs. mid and edge habitat, re-spectively,whilebiomasswas62%(LMM;z = 2.35; p=.048)and

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131%(z=3.84;p<.001)higher.Fishbiomass, thenumberofdi-atomandfishnodes,thenumberofinvertebrateupperandlowerlinks,andwholenetworkmetricsofconnectance,generalregres-sion slopeand interceptwere all similar across reach types (seeTablesS7,S8).

3.2 | Transitional responses within restored reaches

Algal biomasswas lower (LMM; z=−3.42;p=.002) and fish abun-dancewashigherintargetrelativetocontrolreaches(LMM;z = 2.46; p=.036),andbothwere intermediate inrestoredreaches (Figure4;Table S7). Both invertebrate lower- (LMM; z = 13.04; p<.001) andupper-linkanglesincreased(LMM;z = 2.47; p=.031)relativetocon-trols, but not target reaches, indicating the potential for increasedbiomassfluxfrombasalresourcestoinvertebrates,andsubsequentlytofishinrestoredfoodwebs.Thesignificanceofourlink-angletestresultswerenotaffectedwhenweremovedinvertebratelinksuniquetoeachreach(TableS7).Theseresponsessuggestthatrestoredreachfoodwebswere in transition,moving fromcontrol to target condi-tions,asbiomasswasredistributedacrossthenetwork.

3.3 | Invertebrate community structure

Aftercontrollingfordifferencesinabundance(i.e.atbasesamplesizeof1,388),invertebrateα-diversityincreasedbyfivespecies(approxi-mately9%)inrestoredandtargetreachesrelativetocontrols(Table1,Figure5a),and thiswaschieflydue to increases inchironomid taxa

(Table S7). Differences in invertebrate assemblages between habi-tat types (NMDS, r2=0.28, p=.001) revealed that the addition ofLWhabitat enhanced overall β-diversitywithin restored and targetreaches relative to controls (Figure5b, see alsoSupportingResults,FigureS4;TablesS9,S10).

4  | DISCUSSION

ByadoptingaMBACIdesign,wesuccessfullydemonstratedtheposi-tive causal relationships between LW introduction, invertebrate α- diversityandβ-diversity,and linkedthesewithchangesacrossriverfoodwebs,frombasalresourcesthroughtoanapexpredator,S. trutta. The observed consistent ecological responses to restoration acrossrivers contradictmany earlier inferential non-MBACI studieswhichquestionedthe linkbetweenrestoringhabitatdiversityand increas-ingbiodiversity(e.g.Harrisonetal.,2004;Jähnigetal.,2010;Palmeretal., 2010).Moreover, by linking habitat restorationwith changesacrossthefoodweb,ourstudyprovidesamoreholisticsystem-basedview that has been repeatedly called for (Feld etal., 2011; Fribergetal.,2011;Pander&Geist,2013),andwhichsupportstheconceptofLWrewildingasameanstorecoverandconserveriverecosystemsdegradedbyanthropogenicactivities.

Analysis of community mass-abundance scaling relationshipsandfoodwebpropertiesrevealedthatrepopulationfollowingresto-rationwas largelydrivenby invertebrate taxa rare for their size (i.e.thoseconsideredparticularlysensitivetodeterioratingenvironmental

Response Test Estimate SE z value p

Numberinvertebratenodes

Tar–Con 16.05 2.66 6.03 <.001

Res–Con 14.73 3.05 4.83 <.001

Res–Tar −1.32 3.43 −0.38 .921

Invertebratevulnerability Tar–Con 2.18 0.78 2.81 .014

Res–Con 2.49 0.89 2.78 .015

Res–Tar 0.3 1 0.3 .951

Fishgenerality Tar–Con 9.01 2.78 3.24 .003

Res–Con 10.09 3.2 3.16 .005

Res–Tar 1.08 3.59 0.3 .95

Numberbetweeninvertebratelinks

Tar–Con 305.52 54.70 5.59 <.001

Res–Con 301.20 62.82 4.79 <.001

Res–Tar −4.32 70.46 −0.06 .998

Linkagedensity Tar–Con 2.58 0.89 2.89 .011

Res–Con 3.04 1.03 2.96 .009

Res–Tar 0.46 1.15 0.4 .915

Log10 (Salmo trutta abundance+1) (100 m2)

Tar–Con 0.27 0.11 2.54 .029

Res–Con 0.36 0.12 2.90 .010

Res–Tar 0.09 0.14 0.61 .811

Invertebrateα-diversity Tar–Con 4.96 1.69 2.94 .009

Res–Con 4.61 1.93 2.39 .044

Res–Tar −0.34 2.17 −0.16 .986

TABLE  1 Tukey’sall-pairwisecomparisonsofecologicalresponsesbetweencontrol(Con),target(Tar)andrestored(Res)reachesfollowinglinearmixedeffectmodel(LMM)Significantfindingshighlightedinbold

     |  7Journal of Applied EcologyTHOMPSON eT al.

conditions) and with many potential predators. The persistence ofthesepatterns in target reaches indicated that these taxa remainedraredespitehavinghadmoretimetorepopulateoldertargetreaches.Ouranalysis,therefore,providesnovelinsightsintorecoveryprocessesacrossmultiplelevelsoforganisation,fromindividualspeciespopula-tionstothewiderfoodweb,andrepresentsausefulnewmethodforassessingthesuccessofecologicalrestoration.

Byusingasystem-basedapproach,wecanbegintointerprethowan increase in invertebrate α-diversity may influence restored eco-systems. First, reaches restoredwith LW have a higher number ofspecieswhichmay responddifferently to fluctuating environmentalconditions,andthuscouldprovidehigherecologicalredundancythan

in unrestored reaches (Yachi& Loreau, 1999). Second, the elevatedpotentialfornetworkrewiringviaalternativeintermediatenodesandtheincreaseinfeeding-linkdiversitymayhelptoconservespeciesandecosystemprocesses in restoredwebs in the faceofenvironmentalchange (Lu etal., 2016; Staniczenko, Lewis, Jones, & Reed-Tsochas,2010;Tylianakis, Laliberté,Nielsen,&Bascompte,2010).Therefore,riversectionsrewildedwithLWmaybebothmorerobustandresil-ient to environmental stressors. Moreover, because univariate, bi-variateandtrivariateanalyseshaveallowedthequantificationofanarrayofnetworkresponsestoenvironmentalstressorsinrecentyears(Layer etal., 2010; O’Gorman etal., 2012; Thompson etal., 2016;Woodwardetal.,2012),thismoresyntheticapproachcouldprovideanewandwidelyapplicablemeansofgaugingtheecologicalimpactsofarangeofdrivers,includinghabitatrestoration,pollutionandwarm-ing,forexample.Inlightofcurrentandforecastenvironmentalchange,thisisvaluableinformationforpractitionersandstakeholdersaimingtofocusresourcestothemosteffectiveconservationinterventions.

Our findings complement those of previous studies that havedocumented increases in economically important salmonid popu-lations following LW restoration (e.g. Cederholm etal., 1997; Kailetal.,2007;Ronietal.,2015).Wewereable to show that this re-sponsewasbothrapidandpersistent,drivenbythepresenceofsmallS. trutta inboththerestoredandtargetreaches.ThissuggeststhatLWprovides refugia or nursery habitat.Our analyses also indicate

F IGURE  3 TrivariatefoodwebsfortheRiverLoddon,withnewinvertebratenodes(blackfill)andlinks(darkgrey)highlightedinthe(a)restoredand(b)targetreachesthatwerenotpresentinthecontrolreaches.Nodesrepresentmeanbodymass(M)and numerical abundance (N)ofindividualtaxa;circles=diatomtaxa,squares=invertebratetaxa,diamonds=fishtaxa,greylines=feeding-links.SeeFigureS3forallfoodwebplots.Differencesin(c)residualsfromthegeneralregressionslopebetweeninvertebratenodespresentinallreaches(common)comparedwiththosefoundonlyinrestoredortargetreaches(new)inallrivers.Errorbarsrepresent95%confidenceintervals

Log10(M) (mg)–6 –4 –2 0 2 4 6

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(c) F IGURE  4 Differencesin(a)algalbiomass(aschlorophyll-a)and(b)fishabundancebetweencontrol(Con),restored(Res)andtarget(Tar)reaches,evidentfollowinglinearmixedeffectmodelling(LMM).Errorbarsrepresent95%confidenceintervals,*and+indicatesignificantdifferencesattheα = 0.05 level

Log 10

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8  |    Journal of Applied Ecology THOMPSON eT al.

thatsomebioticresponseswereintransitionintherestoredreaches.Elevatedfishabundance,butnotbiomass,inthetargetreachesrel-ative tocontrolswas intermediated in restored reachessuggestingthatotherfishspecies,besidesS. trutta,useLWasrefugiaornurseryhabitat,butthisresponserequiresseveralyearstodevelop.Power(1992)showedthatincreasedhabitatcomplexity,andconsequentlyincreasedinvertebrateabundanceviaprovisionofrefugiafrompre-dation,increasedtop-downeffectsofinvertebratesonproducers.Inthisstudy,algalbiomass in restoredreacheswasalso intermediatebetween control and target conditions. This could mean elevatedinvertebratepopulations intargetreacheshad increasedtop-downeffectson their resources,but that thisalso takes severalyears todevelop.Theshallowingoffeeding linkanglesprovidesfurtherev-idence of transitional effects, as biomasswas redistributed acrossthe network in restored reaches, and highlights the potential forincreased biomass flux between resources and invertebrates andinvertebrates and fishes. These findings pave the way for futureexperimental investigations using similar methods, combined withmeasuresofecosystemprocessesandextendedtemporalandspatialsampling.Suchanapproachcouldinvestigate:thecausesofvariation

acrossrestorations(e.g.asseeninFigures4and5a,S6);conflictingeffectsofrestorationonbiota(e.g.Langford,Langford,&Hawkins,2012);howrestorationaltersbottom-upandtop-downeffects,bio-mass flux and the distribution of taxa across the foodweb at thehabitat level (e.g.useofLWas refugiaandadditional substratebyfishesanddiatoms,respectively);andhowlonger-termalterationstorestored foodwebstructure (e.g. transient, cyclicalor successionalassemblydynamics)relatetothespatialandtemporalfrequencyoftreefallevents.

By using a rigorous MBACI design to establish causative re-sponses, this study contributes substantially to the evidence basethat LW rewilding can help to restore human-impacted river eco-systems.Critically,wewereabletoisolatevariationcausedbycon-foundingecologicaldrivers,enablingustogetclosertoamechanisticunderstandingofecosystemresponsestohabitatrestoration.Ifthisapproachwereadoptedinfuturestudies,conductedacrossarangeof restoration projects and river systems with extended tempo-ralmonitoring, a valuable open-source database of the short- andlonger-termoutcomesofecologicalriverrestorationcouldbedevel-oped. Suchanapproachwouldoffer apowerfulmeansof improv-ingunderstandingofecologicalprocesses,helptomitigatenegativehumanimpactsonriverecosystemsandenhanceglobalbiodiversityconservation.

ACKNOWLEDGEMENTS

ThispaperisdedicatedtoDaveBrady(NationalTrust)whoinspiredthisstudybyinitiatingaground-breakingLWrestoration;wethankThe John Spedan Lewis Foundation for fundingM.S.A.T.;NaturalEnvironment Research Council (Grant reference: NE/J015288/1)for supporting D.M.P.; Rob Goldsworthy, Terry Lawton, DaveRundleandtheirteamsforundertakingtherestorations,andrespec-tive landowners for access to study sites and permitting restora-tionwork.TheEnvironmentAgency,inparticular,DominicMartyn,JonClarkeandDanHorsley,forsupport;FrancoisEdwards,GavinSimpson,NancyCampbell,JamesHumphries,CharlieHanison,DorisPichler, the late Sasha Fayers,OwenDyke, Ian Patmore, CliffordLeo Harris, Jacob Laws, Flavia Toloni, Dan Carpenter, RosemaryBaileyandMickaelTeixeiraAlvesfortheirinvaluablecontributions.Special thanks to ChristianMulder,Michael Craig and an anony-mousreviewerfortheirconstructivefeedback.

AUTHORS’ CONTRIBUTIONS

M.T.,S.B.,C.S.andG.W.conceivedtheideasanddesignedmethodol-ogy;M.T. collected thedata;M.T., J.A.,C.G. andD.P. analysed thedata;M.T.ledthewritingofthemanuscript.Allauthorscontributedcriticallytothedraftsandgavefinalapprovalforpublication.

DATA ACCESSIBILITY

Data available from the Cefas datahub https://doi.org/10.14466/ cefasdatahub.43(Thompson,2017).

F IGURE  5 Differencesin(a)invertebrateα-diversityincontrol(Con),target(Tar)andrestored(Res)reaches(basesamplesize=1,388),evidentfollowinglinearmixedeffectmodel(LMM).Errorbarsrepresent95%confidenceintervals.*Asignificantdifferenceattheα=0.05level.(b)Withinreachdifferencesininvertebrateβ-diversitybetweenhabitattypesusingnon-metricmultidimensionalscaling(NMDS)ofchord-normalisedexpectedspeciessharedindexofdissimilarity(CNESS)dissimilarity(m=16)basedonrestoredandtargetdatarepresentedbySEellipses

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     |  9Journal of Applied EcologyTHOMPSON eT al.

ORCID

Murray S.A. Thompson http://orcid.org/0000-0002-9567-175X

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SUPPORTING INFORMATION

Additional Supporting Information may be found online in thesupportinginformationtabforthisarticle.

How to cite this article:ThompsonMSA,BrooksSJ,SayerCD,etal.Largewoodydebris“rewilding”rapidlyrestoresbiodiversityinriverinefoodwebs.J Appl Ecol. 2017;00:1–10. https://doi.org/10.1111/1365-2664.13013