Interplay between abiotic factors and species assemblages mediated by the ecosystem engineer

18 Pages·2017·1.77 MB·English

by  Auriane G. Jones

Estuarine,CoastalandShelfScience200(2018)1e18
ContentslistsavailableatScienceDirect
Estuarine, Coastal and Shelf Science
journal homepage: www.elsevier.com/locate/ecss
Interplay between abiotic factors and species assemblages mediated
by the ecosystem engineer Sabellaria alveolata (Annelida: Polychaeta)
Auriane G. Jones a,b,c,*, Stanislas F. Dubois a, Nicolas Desroyb, Je(cid:1)ro^me Fournierc,d
aIFREMER,CentredeBretagne,DYNECOLEBCO,29280Plouzan(cid:1)e,France
bIFREMER,EnvironnementetRessourcesBretagnenord,38rueduPortBlanc,BP80108,35801Dinardcedex,France
cCNRS,UMR7208BOREA,61rueBuffon,CP53,75231Pariscedex05,France
dMNHN,StationdeBiologieMarine,BP225,29182Concarneaucedex,France
a r t i c l e i n f o a b s t r a c t
Articlehistory: Sabellaria alveolata is a gregarious polychaete that uses sand particles to build three-dimensional
Received1February2017 structuresknownasreefs,fixedatoprocksorbuiltonsoftsediments.Thesestructuresareknownto
Receivedinrevisedform modifythelocalgrain-sizedistributionandtohostahighlydiversifiedmacrofauna,alteredwhenthe
4October2017
reefundergoesdisturbances.Thegoalofthisstudywastoinvestigatethedifferentsedimentaryand
Accepted6October2017
biologicalchangesassociatedwiththepresenceofaS.alveolatareefovertwocontrastingseasons(late
Availableonline7October2017
winter and late summer), and how these changes were linked. Three different sediments were
considered: the engineered sediment (the actual reef), the associated sediment (the soft sediment
Keywords:
surroundingthereefstructures)andacontrolsoftsediment(i.e.noreefstructuresincloseproximity).
Honeycombworm
Macrobenthos Univariate and multivariate comparisons of grain-size distribution, soft sediment characteristics
Benthicprimaryproduction (organic matter content, chlorophyll a, pheopigments and carbohydrate concentrations) and macro-
Habitatdisturbance fauna were conducted between the different sediment types at both seasons and between the two
Silt seasonsforeachsedimenttype.Adistance-basedredundancyanalyses(dbRDA)wasusedtoinvestigate
Betadiversity thelinkbetweenthedifferentenvironmentalparametersandthemacrofaunaassemblages.Finally,we
France focusedonadisturbancecontinuumoftheengineeredsedimentsproxiedbyanincreaseinthemud
Brittany
presentinthesesediments.Theeffectsofacontinuousandincreasingdisturbanceontheassociated
MontSaint-MichelBay
faunawereinvestigatedusingpairwisebetadiversityindices(SørensenandBray-Curtisdissimilarities
andtheirdecompositionintoturnoverandnestedness).Resultsshowedasignificanteffectofthereef
on the local sediment distribution (coarser sediments compared to the control) and on the benthic
primary production (higher in the associated sediments). At both seasons, S. alveolata biomass and
sedimentprincipalmodeweretheenvironmentalparameterswhichbestdifferentiatedtheengineered,
associated and control sediment assemblages. These two parameters are under the ecosystem engi-
neer's influence stressing its importance in structuring benthic macrofauna. Furthermore, in late
summerbutnotinlatewinter,presence/absenceandabundance-basedbetadiversitywerepositively
correlatedtoourdisturbanceproxy(mudcontent)atendencydrivenbyaspeciesreplacementanda
riseintheassociatedfaunadensity.OurfirstsetofresultshighlighttheimportanceofS.alveolatareefs
asbenthicprimaryproductionenhancersviatheirphysicalstructureandtheirbiologicalactivity.The
resultsobtainedusingbetadiversityindicesemphasizetheimportanceofrecruitmentinstructuring
the reef's macrofauna and e paradoxically e the ecological value of S. alveolata degraded forms as
biodiversityandrecruitmentpromoters.
©2017ElsevierLtd.Allrightsreserved.
Abbreviations:MSMB,MontSaint-MichelBay;MPB,Microphytobenthos;TOM, 1. Introduction
Total organic matter; Chl a, Chlorophyll a; Pheo, Pheopigments; Ins, Insoluble
carbohydrates; Sol, Soluble carbohydrates; dbRDA, Distance-based redundancy
Ecosystemengineersareorganismscapableofmodifyingtheir
analysis;CPUE,Catch-per-unit-effort.
* Corresponding author. IFREMER, Centre de Bretagne, DYNECO, Laboratoire local environment through their physical presence (i.e. autogenic
d’Ecologie Benthique Co^tie(cid:3)re (LEBCO), ZI Pointe du Diable, CS 10070, 29280 engineers)and/ortheirbiologicalactivity(i.e.allogenicengineers),
Plouzane(cid:1),France. “directly or indirectly modulating the availability of resources to
E-mailaddress:[email protected](A.G.Jones).
https://doi.org/10.1016/j.ecss.2017.10.001
0272-7714/©2017ElsevierLtd.Allrightsreserved.
2 A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18
otherspecies”(Jonesetal.,1994).Ultimately,thesespeciesmain- theEuropeancoast(i.e.MSMBandBourgneufBayinFrance)(Holt
tain,modify,createorevendestroyhabitats(Boumaetal., 2009; et al., 1998). Nonetheless, they constitute exceptional locations
Jonesetal.,1994).Theabioticmodificationscausedbyecosystem composed of two distinct entities: the actual three-dimensional
engineerscanleadtofacilitationforsomeorganisms(Hackerand reef structures (engineered sediment), which is spatially discon-
Gaines,1997) and inhibitionthrough negativespecies interaction tinuousandthesoftsedimentpresentbetweenthereefstructures
for others (Bouma et al., 2009; Jones et al., 1997). Nonetheless, (associated sediment) (Desroy et al., 2011). Several kilometers
bioengineered habitats are often reported tohost a morediverse separate them from the nearest rocky shore which signifies, in
species assemblage than the adjoining non-engineered habitats contrast to the veneer form of S. alveolata structures, complete
(Ataide et al., 2014; De Smet et al., 2015; Jones et al., 1997; isolationfrommostofthejuvenileandadultfaunainhabitingthese
Stachowicz, 2001). Physical ecosystem engineering appears to be rocky shores. Furthermore, their physical borders are easy to
particularly important where the environment is extreme (e.g. visualizeagainstthesurroundingsoftsediment.Thesesitesgiveus
thermic, hydrodynamic and/or hydric stress), like in temperate the chance to study different components of S. alveolata's engi-
intertidalareas(Boumaetal.,2009;Jonesetal.,1997).Indeed,ac- neeringeffect(Passarellietal.,2014;Wrightetal.,2006).Thisen-
cordingtoJonesetal.(1997,1994),theseextremeconditionsmight gineering effect can be seen from both an environmental and a
have favored the selection of “extended phenotype engineers” biological perspective by looking at how the ecosystem engineer
through enhanced survival of the engineer and the cohabiting modifiesthelocalsedimentarycharacteristicsandhowthebiodi-
fauna (Dawkins, 1982). These engineer species create complex versitychangesbetweenacontrolsediment,theassociatedandthe
habitatsthatreducelocalpressuressuchaspredationorthermal engineered sediments. The control soft sediment represents the
stress, whilst increasing biodiversity (Bouma et al., 2009). Ulti- baseline or the unmodified state before the honeycomb worms
mately, such favorable environmental changes can lead to an start building reefs, hence representing a new structural state
interestingparadoxwhere“thespatialextentoftherealizedniche (Jonesetal.,2010).
ofaspeciescanbelargerthanthespatialrangepredictedbythe This biogenic habitat is not structurally homogenous, mainly
fundamental niche” as described by Bruno et al. (2003) and re- due to multiple disturbances; direct natural disturbances such as
portedformusselsandbarnaclesinAscophyllumnodosumcanopies stormsandcoldwinters,directanthropogenicdisturbancessuchas
byBertnessetal.(1999). tramplingandindirectanthropogenicdisturbancesthroughshell-
Temperate coasts host a striking number of ecosystem engi- fishfarmingandcoastalengineering.Thesedisturbancesleadtoa
neeringspecies,spanningfrommollusks(forareviewseeGutie(cid:1)rrez gradual modification of the reef visible through disaggregation,
etal.(2003))andpolychaetes(e.g.Laniceconchilega(DeSmetetal., increasingfinesediments,decreasingecosystemengineerdensity
2015)) to canopy-forming algae (e.g. Ascophyllum nodosum andincreasingepibiontcover,causinganumberofchangesinthe
(Bertnessetal.,1999)).AlongtheEuropeancoastline,aparticular associatedfauna(Duboisetal.,2006b,2002;Plicantietal.,2016).
ecosystem engineer has the ability to build three-dimensional Modifications of the associated fauna have been investigated in
structures on top of sediments qualified as reefs (Holt et al., severalcategoricalwaysbutneveralongadisturbancecontinuum
1998).Thisspeciesisacommongregarioustubiculouspolychaete (Duboisetal.,2006b,2002;Plicantietal.,2016).Tounderstandthe
calledSabellariaalveolata,a.k.a.thehoneycombworm.Itgenerally changesintheassociatedfaunaalongthiscontinuum,wechoseto
livesintheintertidalzonefrommidtolowtidelevelsandcanbe focusonthebetadiversityseenas“theextentofchangeincom-
found from Scotland and Ireland to Morocco (Muir et al., 2016). munity composition” as defined by Whittaker (1960) and on an
Sabellaria alveolata uses sand particles remobilized bywaves and abundance-baseddissimilaritymeasurementusingtheBray-Curtis
tidalactiontobuildthetubeinwhichitlives(LeCametal.,2011). dissimilarity.AnalyzingbetadiversityinaS.alveolatareefcanhelp
SincethepelagiclarvaeareattractedbytheL-dopapresentinthe us understand the functioning of this biogenic habitat and give
organic cement produced by the adult worms for their tube- more relevant information to decision makers regarding conser-
buildingactivity,theywilltendtosettleonexistingreefs(Pawlik, vationissues.First,takingintoaccountthethreepreviouslydefined
1988; Wilson, 1968). This phenomenon coupled with favorable sedimenttypes(control,associatedandengineeredsediments),we
environmental conditions(i.e. grain-size structure, hydrodynamic tested in a categorical way, the following hypotheses: (1) the
processes,foodavailabilityandwatertemperature)canleadtothe engineered sediment affects the different sedimentarycharacter-
development of large biogenic reefs (Holt et al., 1998). These istics of the associated sediment, especially grain-size, organic
structures are commonly found on rocky substrata as veneers or mattercontent and microphytobenthos and (2) the diversityand
hummockswheretheyrarelyexceed50cminheightforafewtens species composition of both the engineered and the associated
ofsquaremetersbutinsomerareinstances,theycanbefoundin sedimentsaredifferentfromthecontrolsediment.Wealsolooked
soft bottom areas where theycan grow up to 2 m in height and into potential changes between late winter and late summer,
severalhectaresinsize(Holtetal.,1998;Noernbergetal.,2010). regardingsedimentcompositionandmacrofaunaassemblagesfor
Thelargestoftheseformations,whichisalsothelargestbiogenic each sediment type. Then, using beta diversity and dissimilarity
habitatinEurope,islocatedintheMontSaint-MichelBay(MSMB) measurements,wetestedthefollowinghypothesis:anincreasing
inFrance(Desroyetal.,2011;Duboisetal.,2002). disturbanceoftheengineeredsedimentpromotes(1)betadiversity
The research around this species has mainly focused on its and more specifically species turnover and (2) abundance-based
physiology (i.e. reproduction, fecundity, feeding mode) (Dubois dissimilarityandmorespecificallyabundancegradients.
et al., 2003, 2005, 2006a, 2009) and its tube building activity
(Fournieretal.,2010;LeCametal.,2011).Otherstudieshavelooked 2. Materialsandmethods
intotheecologyofreefswithaparticularinterestontheassociated
fauna (Dias and Paula, 2001; Porta and Nicoletti, 2009; Schlund 2.1. Studyarea
et al., 2016) and factors influencing it such as the reef's different
growthstages(Duboisetal.,2002),epibionts(Duboisetal.,2006b), ThisstudytookplaceinthecentralpartoftheMSMBwherethe
human trampling (Plicanti et al., 2016) and ecological status largestbioconstructioninEuropeislocated;theSainte-Annereef
(Desroyetal., 2011).A largepartof thesestudies has focused on (48(cid:1)380700N and 1(cid:1)400100W), built by the honeycomb worm
Sabellariaalveolatareefson rockysubstrata andnoton soft sedi- Sabellariaalveolata(Desroyetal.,2011).Thisreefissituatedinthe
ment.Reefsdevelopingonsoftsedimentarefarlessfrequentalong lowerintertidalzone(i.e.betweenthe-2andthe-4misobaths
A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18 3
(Noernbergetal.,2010)),paralleltothecoastandtothedominant at each station, six samples separated by at least 5 m were
tidalcurrentsandalsonearimportantbluemussel(Mytilusedulis) randomly taken at low tide. The first three samples were done
cultures.In2014,themaximaldimensionsoftheSainte-Annereef using a 18.5 cm side corer (269 cm2) to a depth of 15 cm (core
were2.5kminlengthfor1kminwidthandtheengineeredsedi- samples).Forengineeredsediments,thisdepthcorrespondstothe
ment represented about 32 ha for about 128 ha of associated layerwhereSabellariaalveolataandmorethan90%ofallspecies
sediment(unpublishedresults).Thearealocatedinthecentralpart live(Duboisetal.,2002).Theotherthreesamplesweredoneusing
ofthebayandalongthesameisobathasthereefischaracterizedby a1m2quadratinordertoestimatetheoverdispersedmacrofauna,
medium to muddysands (Bonnot-Courtois et al., 2009) and bya mainly composed of bivalves and gastropods (quadrat samples).
speciespoor“Macomabalthicacommunity”(Duboisetal.,2002). Allengineeredsedimentsamples(coreandquadratsamples)were
taken at least 1 m from the reef edge to avoid a known border
2.2. Samplingdesignandlaboratoryanalyses effecton themacrofaunadiversity(Gruet,1972), whilethe asso-
ciatedsedimentsamples(coreandquadratsamples)weretakenat
Twosamplingareasweredefined;theSainte-Annereefareaand least 1 m away from the reef structures. The soft sediment core
acontrolarea.Thereefareawascomposedoftwosedimenttypes, samplesweresievedthrougha1-mmsquaremeshonsitewhile
theengineeredandtheassociatedsediments(Fig.1).Thecontrol the engineered sediment core samples were taken back to the
areawasasoftsedimentzonelocated1.5kmNorth-Eastofthereef laboratory where they were broken apart under water and the
areaandonthesamebathymetriclevel.Itwascharacteristicofthe faunaretainedona1-mmsquaremeshwascollected.Associated
medium to muddy sands found in this part of the bay (Bonnot- andcontrolquadratsamplesweredonebysievingonsitethefirst
Courtoisetal.,2009).Samplingtookplaceoveratwo-dayperiod 5 cm of sediment through a 5-mm square mesh. For the engi-
in late winter (late February) and late summer (late September). neered quadrat samples, we sampled by hand all the visible
Thesetwoseasonswerechosenbecausetheyarehighlycontrasted macrofaunalocatedonthereefandinsidethereefinterstices.All
environmentally(e.g.hydro-sedimentaryfeatures)andbiologically coreandquadratsampleswerefixedina5%formaldehydesolu-
(e.g.recruitmentpatterns,speciesturnover,growthrates).Indeed, tion, after which all the macrofauna was sorted, counted and
winterisaperiodoflowbiologicalactivityandhighenvironmental identified to the species or genus level (except for nemerteans,
pressures(coldtemperatures,windandstorms)whilelatesummer oligochaetes and nematodes) and finally preserved in a 70%
is a post-recruitment period with a higher biological activity ethanol solution. For each engineered sediment core sample, all
(ArbachLeloupetal.,2008;Cugieretal.,2010).Hence,samplingat theSabellariaalveolatawereweighted(totalwetweight).
thesetwoseasonshelpsustohaveamorecompletepictureofthe To look at how the ecosystem engineer modifies its environ-
dynamicshappeninginourdifferentstudyzones. ment,werandomlycollectedthreesedimentsamplesforgrain-size
ToinvestigatetheeffectsofS.alveolataondiversityandspecies distribution,totalamountoforganicmatter(TOM),pigmentcon-
composition, we compared the macrofauna associated with the centration (i.e. chlorophyll a and pheopigments) and total carbo-
three different sediment types: the S. alveolata reefs, the sedi- hydrateconcentration(i.e.solubleandinsolublecarbohydrates),at
mentspresentaroundthesestructuresandthecontrolsoftsedi- each associated and control sediment station. For the grain-size
ments. For each sediment type (i.e. engineered, associated and distribution, the first 5 cm of sediments were sampled using a
control sediment, Fig.1), ten stations were sampled. Everyengi- smallplastic core (19cm2). Foralltheothersedimentarycharac-
neeredsedimentstationwaspairedwithanassociatedsediment teristics,onlythefirstcentimeterofsedimentwassampledusinga
station,inordertoinvestigatehowthereefstructuresmodifythe plastic petri dish (57 cm2). Additional samples were collected in
adjoiningsoftsediment.Thestationswereatleast75mapartand order to characterize the sediments constituting the Sabellaria
Fig.1. Schematicoverviewpresentingthehabitatmodificationscausedby(1)theestablishmentofanecosystemengineerand(2)disturbancesoftheengineeredsediment.
RecruitmentofS.alveolataleadstotheformationofabiologicallymodifiedsediment(engineeredsediment)andtoasoftsedimentundertheinfluenceoftheengineeredsediment
(associatedsediment).Engineeredsedimentthenfacedirect(e.g.trampling,storms)and/orindirectdisturbances(e.g.shellfishfarming)whichcanleadtoagradualalteration.
4 A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18
alveolatatubesaswellasthesedimentspotentiallytrappedwithin groupingofengineeredsedimentsamples.Speciespresentinonly
thebiogenicstructure.Theseconsistedinrandomlycollectingthree onesample(i.e.inlessthan2%ofallsamples)wereexcludedfrom
small reef parts (about 8 (cid:3) 3 cm) in each engineered sediment the initial matrix. To identify species typifying each sediment,
station. Sediment grain-size distribution was obtained by me- speciesthatcorrelatedmorethan60%withoneofthefirsttwoaxes
chanical sieving using AFNOR calibrated sieves (from 25 mm to (i.e.Spearmancorrelations)wereplottedoneachPCO.Inparallel,a
63 mm) and granulometric parameters were estimated using the one-way univariate permutational ANOVA (permanova) was per-
‘G2Sd’ package in R v. 3.3.0 (Fournier et al., 2014). Prior to me- formed on the same species density matrices as for the PCOs, in
chanicalsieving,theengineeredsedimentswerecautiouslybroken ordertoevaluateiftherewasasignificantdifferenceinthespecies
intotheiroriginalelements,i.e.mostlybioclastsasevidencedinLe compositionofeachsedimenttype.
Cametal.(2011).Foralltheotheranalyses,thesedimentswerefirst Finally, the macrofauna diversity of each replicate (core and
freeze-driedinordertoworkondrymatter.TOMwasdetermined associatedquadrat)sampledinlatewinterandlatesummer,was
asthedifferencebetweentheweightoffreeze-driedsedimentand assessedusingHill'sindices;N0(numberofspecies),N1(exp(H0)
theweightafter4hat450(cid:1) (AminotandKerouel,2004).Pigment where H0 is the Shannon-Winner diversity (loge)) and N2 (1/D
concentrations (mg.g(cid:4)1 dry sediment) were estimated using the whereDistheSimpson'sdominanceindex(Hill,1973))asrecom-
monochromatic technique (Lorenzen, 1967) described in Aminot mended by Gray (2000) and the total macrofauna density. These
and Kerouel (2004). The chlorophyll a (Chl a) concentration was indicesinformhowthetotalabundanceispartitionedbetweenthe
used as a proxy for microphytobenthos (MPB) biomass (Jeffrey differentspecies(Gray,2000;Whittaker,1972fordetails).Densities
etal.,1997)whilepheopigments(Pheo)concentrationgaveusin- calculated using the CPUE method and for 1 m2 as previously
formationabouttheamountofdegradedphotoautotrophs.Soluble detailed,wereusedtocalculateN1andN2.Foreachreplicate,N0
carbohydrates (Sol) present in the sediment were extracted by wascalculatedasthesumofthespeciesrichnessrecordedinthe
hydrolysis(100(cid:1)Cfor45min),afterwhichthepelletsweretreated core andthespecies richnessrecorded inthe associated quadrat.
with sulfuric acid (H2SO4) and placed 4 h at 100 (cid:1)C in order to ForN0,N1andN2,S.alveolatawaseitherkeptorremovedfromthe
obtaintheinsolublecarbohydrates(Ins).SolandInsconcentrations initialdatainordertoinvestigatehowthisspeciesinfluencesthe
(mg.g(cid:4)1drysediment)werethenestimatedbycolorimetricphenol partitioningoftheassociatedfaunaabundance.
sulfuricdosage(Duboisetal.,1956).Solwereconsideredasbeing To test for significant differences between the three sediment
an important labile source of carbon for consumers living in the typesforthedifferentgrainsizeandmacrofaunadescriptorsand
sediment such as bacteria and deposit-feeding invertebrates becausenoneofthedescriptorsfulfillednormalityofdistribution
(Bellingeretal.,2009)whiletheinsolublecarbohydratestosoluble and homogeneityof variance, permanovas were performed, with
carbohydratesratio(Ins/Sol)wasusedasaproxyfortheC/Nratio sediment type considered as a fixed factor. We used Euclidian
andasaTOMdegradationindex(Delmas,1983). distanceasadistancemeasureandran9999permutationsforeach
test.Ifthemaintestwassignificant,pairwisetestswereperformed.
2.3. Dataanalysis Effectofthepresenceoftheengineeredsedimentonsoftsediment
environmental parameters (TOM, Chl a, Pheo and Ins/Sol) was
2.3.1. Biologicalandenvironmentalengineeringeffects investigated by comparing these parameters between associated
Sincemacrofaunawassampledusingtwodifferenttechniques andcontrolsediments,alsousingpermanovas.Priortoperforming
(coresandquadrats),densitiesofspecieswereestimatedusingthe permanovas, we tested for homogeneity of dispersions using the
catch-per-unit-effort (CPUE) method, i.e. the ratio between the PERMDISPPRIMERroutine(Andersonetal.,2008).Whenrawdata
totalcatchandthetotalamountofeffortusedtoharvestthecatch presented significantly different dispersions between the three
(Skalskietal.,2005).Atonesamplinglocation,whenaspecieswas sedimenttypes(p<0.05),itwaslogtransformed(inlatewinter:
onlycollectedbycoreorquadrat,itsdensitywasestimatedusing principal mode, TOM, Chl a, Pheo, macrofauna density with and
thecorrespondingsamplingsurface.However,whenaspecieswas withoutS.alveolata,N0withandwithoutS.alveolataandN2with
sampledbybothmethods,cumulatedabundancesweredividedby S.alveolata,inlatesummer:macrofaunadensitywithandwithout
thesumofeachgear'sCPUE.Thisestimationmethodwasusedfor S. alveolata, N0 with and without S. alveolata and N1 without
17speciesinlatewinterand15inlatesummer,takingintoaccount S.alveolata).Whenlogtransformationdidnotleadtohomogenous
allthreesediment types.Species'densitieswerecalculated using dispersions(inlatewinter:%mud,%sandandSol,inlatesummer:
theformula: TOM, Chl a, Sol, N1 and N2 calculated with S. alveolata), non-
parametric statistical tests were performed (Kruskal-Wallis test
(cid:1) (cid:3)
ðabundanceAqþabundanceAcÞ forthegranulometricandmacrofaunaparametersandWilcoxon-
densityA ind:m2 ¼
ðCPUEqþCPUEcÞ Mann-Whitneyfortheotherenvironmentalparameters).
Inordertoevaluateifthedifferentenvironmentalandmacro-
where densityA is species' A abundance per m2, abundanceAq is faunaparametersweresignificantlydifferentbetweenlatewinter
species'Aabundanceusingthequadrat,abundanceAcisspecies'A and latesummer for each sediment type, one-factor permanovas
abundance using the core, CPUEq is the quadrat's catch-per-unit- wereperformed,withseasonconsideredasafixedfactor.Wechose
effort (1 m2) and CPUEc is the core's catch-per-unit-effort to perform one-factor rather than two-factor univariate analysis
(0.0269m2). of variance (in this case with sediment type and season as fixed
To assess the effect of Sabellaria alveolata on the associated factors), because we lacked replication inside each season for
macrofauna and validate our a priori grouping into engineered, our different sediment types (Underwood, 1997). As previously
associated and control sediments, Principal Coordinates Analysis mentioned, permanovas (9999 permutations) were used rather
(PCO) were performed for the late winter and late summer data thant-testsbecausenoneof theinvestigatedvariableswerenor-
sets. Analyses were performed on a Bray-Curtis similarity matrix mally distributed. Homogeneity of dispersions was also tested
calculated from log-transformed densities after S. alveolata was (PERMDISP) and data was transformed when necessary (square-
removed from the matrix, in order to take into account only the root transformation for TOM in the associated sediments, log
speciesassociatedwiththissedimenttype.Indeed,becauseofits transformation for macrofauna density with S. alveolata in the
highabundance(i.e.onaverage,63% of thetotalabundance),the controlsedimentsandformacrofaunadensitywithoutS.alveolata
singlepresenceofS.alveolatawouldautomaticallycauseastrong intheengineeredsediments).ThePermanovas,PERMDISProutines
A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18 5
andPCOswereperformedusingthePRIMERv6softwarewiththe among regions (Bennett and Gilbert, 2016). We chose to use the
PERMANOVAþadd-on(Andersonetal.,2008).Post-hocKruskal- presence/absence based indices presented by Baselga (2010) in
Wallis tests were performed with the ‘kruskalmc’ function from order to partition total beta diversity, expressed by Sørensen
the‘pgirmess’package(Giraudoux,2016)usingRversion3.3.0(R dissimilarity (bsor), into the turnover (bsim) and nestedness (bnes)
CoreTeam,2016). components. In this case, bsor ¼ bsim þ bnes. Under conditions of
equalspeciesrichness,bsor¼bsimandbnes¼0,whileundercon-
2.3.2. Linkingenvironmentalandbiologicalengineeringeffects ditions of unequal species richness, bsim and bnes vary between
Therelationshipbetweentheenvironmentalcharacteristicsand 0 and bsor. Sørensen dissimilarity varies between 0 and 1, with
the macrofauna present in the three sediment types wasinvesti- 0 indicating that two samples have identical species list and 1
gated using distance-based linear models (DistLM). In line with indicatingnocommonspecies(Baselga,2010).Forbsim,0indicates
LegendreandAnderson(1999)andMcArdleandAnderson(2001), completenestedness,andamaximalvalueof1canbefoundifin
DistLM models were coupled to a distance-based redundancy oneofthetwoconsideredsamples,therearenospeciesrecorded
analysis (dbRDA) to define the best fitted model in a multi- and in the other, the number of species is maximal (Koleff et al.,
dimensional space in awaysimilar toa constrained PCO.DistLM 2003). To have a complementary vision of how disturbance
modelswerebuiltusingtheBayesianInformationCriterion(BIC)to affected the associated fauna abundance, the abundance-based
identify“good”modelsandthe‘best’proceduretoselectthevari- dissimilarity (Bray-Curtis dissimilarity, dBC) was also partitioned
ablesaccordingtotheBIC.PriortotheDistLManddbRDAanalysis, intobalancedchangesinabundance(dBC-bal)andabundancegra-
the environmental parameters were displayed using Draftsman dients(dBC-gra),whicharecloselyrelatedtoturnoverandnested-
plotsandtheonespresentinganimportantskewnessweretrans- nesscomponentsrespectively(Baselga,2013).Theseindiceswere
formedtoapproachnormality(Andersonetal.,2008).Iftwopre- computed after removing S. alveolata from the presence/absence
dictorvariableswerestronglycorrelated(r2>0.80),oneof them and density matrices. They were calculated using the pairwise
wasremovedfromtheanalysisinordertoavoidmulti-collinearity measuresinordertohavethebetadiversityandthedissimilarities
(Dormann et al., 2013). Except for the grain-size data, environ- foreachpairofsamples(i.e.435pairs).Then,usingEuclidiandis-
mental parameters used to characterize an engineered sediment tance, all the mud content pairwise differences were calculated.
samplewerethesameasforitscorrespondingassociatedsediment Finally, using the different pairwise measures, we performed
sample.Forlatewinter,thefinalpredictordatasetcontainedthe% Manteltests(9999permutations)forlatewinterandlatesummer
sand, Pheo (both square-root transformed), % mud, TOM, data,totestthenullhypothesisofnorelationshipbetweenthemud
S. alveolata biomass (all three fourth-root transformed), principal contentdistancematrixandeachbetadiversitymatrix.Ap-value
modeandIns/Sol(bothlogtransformed).Forlatesummer,thefinal below 0.05 indicates a significant correlation between the two
predictordatasetwasthesameasforlatewinter,exceptthe%sand investigated distance matrices, with the sign of the r-value indi-
which was removed (absolute correlation with % mud > 0.8). cating if the twomatrices are positivelyor negativelyassociated.
S.alveolatabiomasswasusedratherthanabundancebecausethis The beta diversity indices were computed using the ‘beta.pair’
parameterprovidesmoreinformationaboutecosystemfunctioning function, and the Bray-Curtis dissimilarity indices using the
(Cardinale et al., 2013). S. alveolata biomass was considered as a ‘bray.part’ function, both from the ‘betapart’ R package (Baselga,
predictorvariablesinceitphysicallymodifiesitsenvironmentand 2013). The Mantel tests were performed using the ‘mantel.rtest’
it was consequently removed from the macrofauna data set. The functionfromthe‘ade4’Rpackage(DrayandDufour,2007).
DistLM models and dbRDA analysis were performed using the Totestthelinkbetweenthemacrofaunalassemblagesbasedon
PRIMER v6 software with the PERMANOVA þ add-on (Anderson their respective beta diversity and dissimilarity indices and the
etal.,2008). disturbance parameter (i.e. mud content), non-metric multidi-
mensional scaling ordinations (nMDS) were successively per-
2.3.3. Disturbancesandbiologicalengineeringeffect formedforeachindex(bsor,bsim,bnes,dBC,dBC-balanddBC-gra)andat
Atitsclimax,aS.alveolatareefisformedby100%honeycomb each sampling period (late winter and late summer) using the
worm tubes, leaving virtually no space for infaunal organisms. ‘metaMDS’functionofthe‘MASS’Rpackage(VenablesandRipley,
When natural or anthropogenic disturbances (e.g. storms, tram- 2002).Then,the‘envfit’function(‘vegan’Rpackage)wasusedto
pling)physicallydamagethereef,tubesaredestroyed,freeingup test if the mud content was significantly correlated with each
space.Thisnewavailablespacecanbefilledeitherwithotheror- ordination(Oksanenetal.,2016).Whenacorrelationwassignifi-
ganisms such as the oyster Magallana gigas (formerly known as cant,themudcontentswerefittedandplottedonthegivennMDS
Crassostrea gigas) or by fine particles. Fine particles accumulate using the ‘ordisurf’ function of the ‘vegan’ R package (Oksanen
fromsuspendedsediments, orfromthefecesandpseudofecesof et al., 2016). All these analyses were performed using R version
S. alveolata and other bivalves (biodeposition) (Dubois et al., 3.3.0(RCoreTeam,2016).
2006b). In eithercase, this finesediment can end uptrapped in-
sidetheS.alveolatareefs.Consequently,theincreaseddepositionof 3. Results
mud inside the engineered sediments is the result of several
different and often concomitant disturbances. Fine sediment 3.1. Environmentalengineeringeffect
depositionhaspreviouslybeenrecognizedasasignificantdistur-
bance to stream macroinvertebrates (Mathers et al., 2017) and Mean values of grain-size distribution parameters measured
benthic habitats (Balata et al., 2007; Mateos-Molina et al., 2015; within each sediment type are reported in Table 1a. Analyses
Milleretal.,2002).Similarly,wechosetoconsidermudcontentasa revealedsignificantdifferencesbetweenthesedimenttypesforall
proxy for disturbance. This proxy was also chosen because it is testedmetricsinlatewinter(p<0.001)andforallbutoneinlate
independent from Sabellaria alveolata population dynamics and summer(mudcontent).Atbothperiods,therewasastrongengi-
physiologicalstate.Finally,usingthemudcontentmakesthetwo neering effect on the principal mode marked by a significantly
seasonsreadilycomparable. coarsersedimentintheengineeredandassociatedsedimentsthan
Beta diversity was calculated using pairwise multivariate dis- inthecontrolsediments(Table1a).Inlatewinter,thesortingindex
tancessincetheyareindependentofsamplesizeandregionaldi- S0 was significantlylowerin the engineered and associated sedi-
versity(gammadiversity)allowingaccuratepotentialcomparisons mentsthaninthecontrolandmudcontentwassignificantlylower
6 A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18
Table1
Meanvalues(±standarderrors)for(a)thegrain-sizeparametersofthethreesedimenttypes(engineered,associatedandcontrol)and(b)theenvironmentalparametersforthe
associatedandthecontrolsediments.Significantdifferences(p<0.05)oftheone-wayANOVAsareinboldandfor(a),post-hocresultsaredesignatedbysuperscriptletters
indicatinghomogenousgroupsofsamples.TOM:totalorganicmattercontent,Chla:chlorophyllaconcentration,Pheo:pheopigmentsconcentration,Sol:solublecarbo-
hydratesconcentration,Ins/Sol:ratiooftheconcentrationofinsolublecarbohydratesonsolublecarbohydrates.
(a) Latewinter Latesummer
Engineered Associated Control p-value Engineered Associated Control p-value
Principalmode(mm) 688±35a 1010±118a 186±8b <0.001 618±8a 692±74a 201±9b <0.001
Sortingindex(S0) 1.71±0.05a 1.72±0.05a 2.97±0.34b <0.001 1.69±0.05a 2.98±0.45b 2.70±0.37b 0.018
Mud(%)(<63mm) 10.00±0.83a 1.84±0.44b 27.38±3.62a <0.001 9.59±1.22a 20.47±5.37a 21.61±5.23a 0.106
Sand(%)(63e200mm) 87.19±0.83a 76.74±1.40b 71.69±3.53b <0.001 85.77±1.40a 65.11±4.09b 76.79±5.17ab 0.001
(b) Latewinter Latesummer
Associated Control p-value Associated Control p-value
TOM(%) 6.96±0.72 2.70±0.30 <0.001 4.91±0.59 2.26±0.28 <0.001
Chla(mg.g(cid:4)1sediment) 12.21±2.49 2.83±0.58 0.0022 13.39±2.24 3.92±0.88 0.002
Pheo(mg.g(cid:4)1sediment) 14.54±0.36 16.18±0.36 0.0014 15.56±0.53 15.41±0.29 0.826
Sol(mg.g(cid:4)1sediment) 442±72 113±25 0.0027 467±78 120±25 <0.001
Ins/Sol 8.59±2.29 8.63±0.37 0.9998 5.96±0.43 6.32±0.33 0.5175
intheassociatedsedimentsthanintheothertwosedimenttypes. (permanova: p ¼ 0.28) probably because of the important vari-
Finally,thesandcontentwassignificantlyhigherintheengineered abilityinlatewinter(Table1).
sediment relative to the other sediment types. In late summer,
associated sediments had a higher sorting index than the engi- 3.2. Biologicalengineeringeffect
neered sediments and one comparable to the control sediments.
Althoughassociatedsedimentswerealsocharacterizedbyahigher In late winter, 9244 organisms belonging to 121 different taxa
mudcontentinlatesummercomparedtolatewinter(permanova: were sampled in the cores and 8478 organisms belonging to 26
p ¼ 0.0051), no significant difference was observed between the differenttaxaweresampledwiththequadrats(seetheAppendixfor
three sediment types. For all grain-size parameters, the control acompletelistofspecies).Comparatively,inlatesummermoreor-
sedimentsshowednosignificantchangesbetweenlatewinterand ganismsandtaxaweresampledwiththecores(23463organisms/
latesummer(permanova:p(principalmode)¼0.23,p(S0)¼0.60, 125taxa)whilefewerorganismsandmoretaxaweresampledwith
p(mud)¼0.37andp(sand)¼0.42).Thepatternwassimilarforthe thequadrats(4677organisms/30taxa).Forallsedimenttypes,total
engineered sediments (permanova: p(principal mode) ¼ 0.059, species richness was consistently higher in late summer than in
p(S0) ¼ 0.78, p(mud) ¼ 0.78 and p(sand) ¼ 0.39). The associated late winter but this differencewas significantonly for the control
sedimentsshowedsignificantchangesintheirgrain-sizedistribu- and engineered sediments (permanova: p(control) ¼ 0.039,
tionbetweenlatewinterandlatesummer.Inlatewinter,theywere p(associated)¼0.071andp(engineered)¼0.0001).
muchmorehomogenousthaninlatesummer(Table1)andthey PCOsandone-waypermanovasperformedondensitymatrices
became significantly muddier between the two sampling cam- indicated that the three sediment types significantly differed
paigns(permanova:p¼0.0051)leadingtoasignificantdecreasein (p < 0.05) in their associated fauna at both sampling periods,
theprincipalmode(permanova¼0.025). confirmingourapriorisedimenttypegrouping(Fig.2andFig.3).
The comparison of sedimentary parameters revealed a strong PCOaxis1explainedinlatewinterandlatesummer,respectively
engineering effect at both periods regarding TOM, Chl a and Sol 26.1 and 30.3% of the total variation present in the resemblance
(Table1b,p<0.005).Inbothseasons,TOMwasconsistentlytwice matrix and clearly separated the engineered samples from the
as high in the engineered environment than in the control zone. control samples. PCO axis 2 explained in late winter and late
Organicmattercontentalsoshowedasignificantdecreasebetween summer, respectively 14.6 and 14.8% of the total variation and
late winter and late summer in the reef zone (permanova: discriminatedtheengineeredandcontrolsamplesfromtheasso-
p¼0.029)andnosignificanttemporalchangeinthecontrolsed- ciated samples. In both seasons, engineered samples werehighly
iments(permanova:p¼0.29).Similarly,Chlaconcentrationwas clusteredcompared tothe more scattered associated and control
tentimeshigherinthesoftsedimentsadjacenttotheengineered sedimentssamples.Inlatewinter,thecontrolandassociatedsed-
structures than in the control and did not displayany significant iments were well separated while there was a small overlap be-
temporalchanges in either the control (permanova: p ¼ 0.29) or tween the associated and engineered sediments (Fig. 2). In late
theassociatedsediments(permanova:p¼0.72).Solconcentration summer,therewasanoverlapbetweentheassociatedandcontrol
was also consistently four times higher in the reef environment sediments (Fig. 3). This overlap was mostly due to bivalves like
thaninthecontrolanddisplayedatemporalstabilitysimilartothe Limecola balthica or Cerastoderma edule and to the polychaete
Chla(permanova:p(control)¼0.87andp(associated)¼0.82).In Nephtyshombergii(Fig.3andAppendix).Finally,engineeredsedi-
latewinter,thePheoconcentrationwassignificantlyhigherinthe ments were characterized by a much greater number of species
control than in the associated sediments while in late summer, correlatedatmorethan60%witheachPCOaxis(11inlatewinter
there was no significant difference. In both sediment types, and17inlatesummer)thantheassociated(3inlatewinterand1in
Pheo concentrations did not show significant changes between latesummer)andthecontrolsediments(3inlatewinterand6in
the two sampling campaigns (permanova: p(control) ¼ 0.10 and latesummer).
p(associated)¼0.11).Finally,Ins/Solwasnotsignificantlydifferent Mean macrofauna diversity indices and densities were calcu-
betweenassociatedandcontrolsedimentsinlatewinterandlate latedwithineachsedimenttypeandforeachsamplingcampaign
summer, andwas significantly higher in latewintercompared to (Table2aandb).Atthesedimenttypescale,one-waypermanovas
latesummerforthecontrolsediments(permanova:p¼0.0001). showedsignificantdifferencesbetweenengineeredsedimentson
Thistemporalpatternwasnotdetectedintheassociatedsediments theonehandandassociatedandcontrolsedimentsontheother,for
A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18 7
allthediversitymeasurementsanddensitiesatbothperiods.There
weretwoexceptionsregardingN1andN2calculatedinlatesum-
merwithS.alveolatatakenintoaccount.Inthesecases,therewere
nosignificantdifferencesbetweenthethreesedimenttypes.When
S.alveolatawastakenintoaccount,totalmacrofaunadensitywas
20timeshigherintheengineeredsedimentsatbothperiods.This
differencewasmaintainedevenafterS.alveolatawasremovedfrom
thedatasetbutitwasreducedtoanaverage5-folddifference.The
engineeredsedimentwasalsohometosignificantlymorespecies
(meanspeciesrichnessN0)thantheassociated andcontrol sedi-
mentsandthis,whateverthesituation.
Regarding macrofauna density, N1 and N2, associated and
control sediments presented similar temporal patterns when
comparing late winter and late summer. Their respective macro-
faunadensityincreasedsignificantlybetweenthetwocampaigns
(permanova:p(control)¼0.023andp(associated)¼0.018)while
N1 and N2 showed non-significant differences (permanova:
p(control-N1) ¼ 0.15, p(control-N2) ¼ 0.25, p(associated-
N1)¼0.83andp(associated-N2)¼0.53).Betweenlatewinterand
late summer, the engineered sediments presented a significant
increase in the total macrofauna density (permanova: p(density
Fig.2. PCOanalysisofmacrobenthosassociatedwiththethreesedimenttypesinlate withS.alveolata)¼0.0001)onlydrivenbyasignificantincreasein
winter.TheanalysisisbasedonBray-Curtissimilaritiesoflogtransformeddensity the associated fauna density (permanova: p(density without
data.Theblackdiamonds,thegreysquaresandthelightgreycirclesrepresentthe S.alveolata)¼0.0001andp(S.alveolatadensity)¼0.54).Theyalso
engineered, the associated and the control sediment samples respectively. Vectors
representspeciescorrelatingmorethan60%withoneofthefirsttwoPCOaxes.The showedasignificantincreaseinthecaseofN1andN2calculated
correlationsarebasedonSpearmancoefficients.ASIM:Acheliasimplex,CEDU:Cera- withS.alveolata(permanova:p(N1)¼0.0007andp(N2)¼0.0001),
stodermaedule,CFOR:Crepidulafornicata,CMAE:Carcinusmaenas,CVOL:Corophium achangewhichwasnotsignificantoncetheengineerspecieswas
volutator,GBOB:Goniadellabobrezkii,GUMB:Gibbulaumbilicalis,GVUL:Golfingiavul- removed(permanova:p(N1)¼0.089andp(N2)¼0.73).
garis, LBAL: Limecola balthica, LLEV: Lekanesphaera levii, LRUG: Lekanesphaera rugi-
cauda, McfGAL: Mytilus cf. galloprovincialis, MFRA: Mediomastus fragilis, MGIG:
Magallanagigas,MPAL:Melitapalmata,NCIR:Nephtyscirrosa,NLAP:Nucellalapillus, 3.3. Linkingenvironmentalandbiologicalengineeringeffects
PCUL:Perinereiscultrifera,PPLA:Porcellanaplatycheles.
DistLM and dbRDA analysis were performed in late winter
(Fig. 4a) and late summer (Fig. 4b) with S. alveolata biomass
considered as an environmental parameter. In both seasons,
S.alveolatabiomasswastheparameter whichbestexplainedthe
relationship between environmental parameters and macrofauna
assemblages(18.0%inlatewinterand24.8%inlatesummer).Inlate
winter,themostparsimoniousmodel,explaining33.6%ofthetotal
variation in species assemblages, was defined by (1) Sabellaria
biomass(square-roottransformed,18.0%),(2)principalmode(log
transformed,13.2%) and (3) total organic matter content (fourth-
roottransformed,10.7%,Fig.4).Thefirsttwoaxesexplained91.6%
of the fitted variation and 30.7% of the total variation. Species
assemblage werestructured according totwo gradients. The first
was driven by S. alveolata, and separated engineered sediments
fromthetwoothertypes.Thesecondwasdrivenbythesediment
principalmodeandthetotalorganicmattercontentandseparated
theassociatedfromthecontrolsediments(Fig.4a).Inlatesummer,
themostparsimoniousmodelexplained40.7%ofthetotalvariation
inspeciesassemblages.Itwasdefinedbythesamefirsttwovari-
ables as for late winter: Sabellaria biomass (square-root trans-
formed, 24.8%) and principal mode (log transformed,16.9%). The
third selected variable differed from late winter since it was the
Fig.3. PCOanalysisofmacrobenthosassociatedwiththethreesedimenttypesinlate
mudcontent(fourth-roottransformed)anditexplainedonlyavery
summer.TheanalysisisbasedonBray-Curtissimilaritiesoflogtransformeddensity
small part of the total variation (0.079%). The first two axes
data.Theblackdiamonds,thegreysquaresandthelightgreycirclesrepresentthe
engineered, the associated and the control sediment samples respectively. Vectors explained87.5%ofthefittedvariationand35.6%ofthetotalvari-
representspeciescorrelatingmorethan60%withoneofthefirsttwoPCOaxes.The ation.Again,speciesassemblageswerestructuredaccordingtotwo
correlationsarebasedonSpearmancoefficients.AECH:Acheliaechinata,ALAE:Achelia gradientsbuttheydidnotseparatethedifferentsedimenttypesas
laevis,ASIM:Acheliasimplex,CEDU:Cerastodermaedule,CMAE:Carcinusmaenas,CVOL: clearlyasinlatewinter.S.alveolatastilldefinedthefirstgradient
Corophiumvolutator,EORN:Eulaliaornata,GBOB:Goniadellabobrezkii,GMAX:Gnathia
maxillaris,GUMB:Gibbulaumbilicalis,GVUL:Golfingiavulgaris,LBAL:Limecolabalthica, andclearlyseparatedtheengineeredsedimentsfromthetwosoft
LCON: Lanice conchilega, LLEV: Lekanesphaeralevii, LRUG: Lekanesphaera rugicauda, sediments. The opposition between the principal mode and the
MARE: Malmgrenia arenicolae, McfGAL: Mytilus cf. galloprovincialis, MFRA: Medi- mudcontentdefinedthesecondgradient.Alongthisgradient,the
omastusfragilis,MGIG:Magallanagigas,MPAL:Melitapalmata,NCIR:Nephtyscirrosa, distinction associated/control sediments was not well defined.
NEMA:Nematodaspp.,NEME:Nemertesp.,NHOM:Nephtyshombergii,NLAP:Nucella
Indeed, there were three associated sediment samples character-
lapillus,NMIN:Nephasomaminutum,OCTE:Odontosyllisctenostoma,PCUL:Perinereis
cultrifera,PPLA:Porcellanaplatycheles. ized by high mud contents and isolated from the rest of the
8 A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18
Table2
Meanvalues(±standarderrors)forthetotalmacrofaunadensity(numberofindividuals.m(cid:4)2),N0,N1andN2with(a)Sabellariatakenintoaccountand(b)Sabellariaexcluded,
forthethreesedimenttypes(engineered,associatedandcontrol)andatbothsamplingperiods(latewinterandlatesummer).N0representsthespeciesrichness,N1the
exponentialoftheShannon-WinnerdiversityandN2theinverseoftheSimpsondominanceindex.Significantdifferences(p<0.05)oftheone-wayANOVAsareinboldand
post-hocresultsaredesignatedbysuperscriptlettersindicatinghomogenousgroupsofsamples.
Latewinter Latesummer
(a)Macrofauna(Sabellariaincludedintheanalyses)
Engineered Associated Control p-value Engineered Associated Control p-value
Density 10067±841a 585±102b 629±109b <0.001 23911±2530a 1029±156b 1403±351b <0.001
N0 17±1a 7±1b 8±1b <0.001 26±1a 9±1b 10±1b <0.001
N1 2.92±0.37a 4.46±0.50b 4.54±0.37b 0.013 6.01±0.65a 4.61±0.38a 5.22±0.28a 0.229
N2 1.87±0.23a 3.75±0.40b 3.60±0.28b <0.001 3.93±0.44a 3.44±0.30a 4.04±0.25a 0.315
(b)Macrofauna(Sabellariaexcludedfromtheanalyses)
Engineered Associated Control p-value Engineered Associated Control p-value
Density 2385±518a 538±91b 629±109b <0.001 11066±1814a 981±137b 1403±351b <0.001
N0 16±1a 7±1b 8±1b <0.001 25±1a 9±1b 10±1b <0.001
N1 7.73±0.51a 4.30±0.49b 4.54±0.37b <0.001 9.00±0.52a 4.51±0.37b 5.22±0.28b <0.001
N2 5.63±0.42a 3.64±0.39b 3.60±0.28b <0.001 5.82±0.38a 3.36±0.30b 4.04±0.25b <0.001
associatedsedimentsamples(Fig.4b). (r2¼41.33%),andbetween20and30%ofbnes(r2¼21.25%)anddBC-
bal (r2 ¼ 29.56%). When the correlationwas significant, the fitted
mud contents were plotted on the corresponding nMDS plots
3.4. Disturbancesandbiologicalengineeringeffect
(Figs.5and6).Thecorrelationbetweenthedisturbanceproxyand
the different nMDS plots showed a pattern similar to the one
Consistent mean values in late winter (10%) and late summer
(9.59%), confirm the choice of the mud content as a suitable revealed by the late summer Mantel test, with beta diversity
‘disturbance parameter’ (Table 1a). Indeed, these values did not changes mainly driven by a species turnover and an abundance
significantlyvarybetweenthetwocontrastedseasonswesampled gradient.
(permanova: p ¼ 0.78). Incontrast,themean S. alveolatadensity
almost doubled between late winter (7682 ± 3312 ind.m(cid:4)2) and 4. Discussion
latesummer(12844±14262ind.m(cid:4)2),withaveryhighsummer
variability,leadingtonosignificantchange(permanova:p¼0.54). 4.1. Engineeredstructurescausegrain-sizedistributionchanges
Oppositely, the mean S. alveolata biomass bysurface unit signifi-
cantlydecreasedbetweenlatewinter(646±317gm(cid:4)2)andlate Environmentalengineeringeffectsarecomposedoftwotypesof
summer(318±211gm(cid:4)2)(permanova:p¼0.0001). changes, structural and abiotic changes, structural changes being
Mantel tests performed between the mud content distance causedbyecosystemengineersandinducingabioticchanges(Jones
matrix and the different beta diversity matrices showed a clear et al., 2010). S. alveolata is capable of biologically modifying soft
temporaldifferencebetweenlatewinterandlatesummer.Thetests sedimentsbyselectivelygluingtogetherbioclasticsandparticles,in
werenotsignificantwhenperformedusingthelatewinterdatasets order to build its tube (Fournier et al., 2010). This leads to the
(p> 0.05,Table3),whiletheyrevealedasignificantandpositive transformationofaninitialsoftsedimentintoathree-dimensional
correlation between the mud content distance matrix and bsor hardsubstratumwithalonglastingresistancetophysicalloading
(p < 0.001, r ¼ 0.24), bsim (p ¼ 0.0066, r ¼ 0.15), dBC (p < 0.001, via the secreted organic cement (Le Cam et al., 2011). Sabellaria
r¼0.38)anddBC-gra(p<0.001,r¼0.29)(Table3)usingthelate alveolata can therefore be considered as a “structural engineer”
summer data sets. These results indicate that in late winter, an according to Berke (2010). Structural changes caused by physical
increaseinmudcontent,usedasaproxyfordisturbance,doesnot ecosystemengineersresultinavariationinthedistributionoffluid
leadtobetadiversitychangesbutinlatesummer,itleadsto(1)an andsolidmaterialtermedabioticchanges(Jonesetal.,2010).Inthe
increaseinbetadiversitydrivenbyaspeciesreplacementand(2) case of S. alveolata, a direct abiotic engineering effect observable
an increase in abundance-based dissimilarity driven byan abun- throughtheengineeredsedimentsandanindirectone,observable
dancegradient.Ordinationplotsofsimilarities(nMDS)ofmacro- throughtheassociatedsediments,weredetected.Engineeredand
faunalassemblagesbasedonbsor,bsim,bnes,dBC,dBC-balanddBC-gra associated sediments presented, at both sampling periods, a
indiceswereperformedinlatewinterandlatesummer(Figs.5and coarsertexturethanthecontrolsediments,confirmingtheimpact
6).Inlatewinter,thecorrelationbetweenthemudcontentandthe Sabellariidaepolychaetes haveonthelocalsediment's texture by
different nMDS plots was significant for bsor (p ¼ 0.008), bnes selecting sand particles of a specific size to build their tubes
(p¼0.023),dBC(p¼0.019)anddBC-gra(p¼0.027).Themudcontent (Phragmatopoma caudata (¼ P. lapidosa) (Gram,1968; Kirtleyand
explained30.67%oftheordinationbasedonbsorand24.54%ofthe Tanner,1968; Main and Nelson,1988), Sabellaria vulgaris (Wells,
ordinationbasedonbnes.Similarly,26.93%and24.51%oftheordi- 1970), Sabellaria nanella (Bremec et al., 2013)). Ultimately, these
nationbasedondBCanddBC-grarespectivelywhereexplainedbythe bioconstructingSabellariidaespeciescreatereefscharacterizedby
mud content. In late summer, the correlation between the mud agrain-sizedistributiondifferentfromthelocalsoftsediments.The
content and the different nMDS plots was significant and much caseoftheassociatedsedimentsraisesthequestionofthedefini-
higher for all the indices; bsor (p ¼ 0.001), bnes (p ¼ 0.036), bsim tionofareefhabitat.InEurope,“reefs”arerecognizedasamarine
(p ¼ 0.001), dBC (p ¼ 0.001), dBC-gra (p ¼ 0.002) and dBC-bal habitat to be protected and are listed under Annex I of the EC
(p ¼ 0.006). Indeed, the mud content explained over 50% of the Habitats Directive (Council Directive EEC/92/43 on the Conserva-
ordinationbasedonbsor(r2¼53.07%)anddBC(r2¼52.76%),around tion of Natural Habitats and of Wild Fauna and Flora) under the
40% of the ordination based on bsim (r2 ¼ 39.23%) and dBC-gra designation of Special Areas of Conservation (SACs). They are
A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18 9
habitats presenting stable sedimentary conditions. The mud pre-
sent in the engineered sediments is located in small cracks and
crevices protected from the main hydrodynamic processes (i.e.
winterstorms,tidalcurrentsandswell).Conversely,theassociated
sedimentsarecharacterizedbyasteepandsignificantincreasein
mudcontentbetweenwinter(2%)andsummer(21%).Asshownby
Calineetal.(1988)fortheSainte-Annereef(MSMB),localizedmud
depositions are linked to hydrodynamic and associated hydro-
sedimentary processes induced by the presence of the reef itself
andofthemusselfarms(bouchots)infrontofthereef(McKindsey
et al., 2011). These mud depositions are observed behind reef
structures important enough to act as physical barriers (Caline
et al., 1988), where they are generally superficial and conse-
quentlyeasilyerodedbystrongwaveaction,limitingtheirpresence
inwinter.
4.2. Engineeredstructuresenhancebenthicprimaryproductionand
potentiallymicrobialactivity
As reported by Jones et al. (2010), abiotic changes induced by
physicalengineeringactivitycanthemselvescausebioticchanges.
Ourresultsclearlyshowthatatbothseasons,associatedsediments
have a higher organic mattercontent compared with the control
sediments. At both seasons, high levels of organic matter were
associatedwithhighchlorophyllaconcentrations,indicatingthat
partoftheorganicmatterpresentintheassociatedsedimentsisthe
consequenceofMPBdevelopment.Thehighbenthicprimarypro-
ductionpromotedbytheSainte-Annereef,comparedtoagenerally
lower benthic production in the MSMB as measured by Davoult
etal.(2008)andMigne(cid:1)etal.(2009),confirmsitsimportantbiotic
engineering effect. Similar results were found for the invading
intertidal reef-forming polychaete Ficopomatus enigmaticus
(Bruschettietal.,2011),forshallowoysterreefs(Crassostreavirgina,
Newell et al., 2002) and for intertidal mussel beds (Engel et al.,
2017). According to Berke (2010), “structural engineers operate
through similar processes and have similar types of effects”.
Consequently,thecreationofbenthicprimaryproductionhotspots
byreef-buildingstructuralengineerscouldbeageneralpropertyof
thesemarinespecies.Nonetheless,thisphenomenonwasobserved
at the scale of the largest and probablyoldest S. alveolata reefin
Europe(AudouinandMilne-Edwards,1832)andthestudybyEngel
etal.(2017)highlightedtheimportanceofthesizeandageofthe
bioconstruction in promoting local benthic microalgae. Hence,
furtherstudiesareneededtoconfirmthegeneralroleofS.alveolata
reefsas“biologicalpowerstations”(Engeletal.,2017).
Fig.4. dbRDAplotsbasedona)thelatewinterdatasetandb)thelatesummerdata
Furthermore,thehighchlorophyllaconcentrationsmeasuredin
setandrepresentingthethreesedimenttypemacrofaunacompositionasexplainedby
thesetofenvironmentalparameterscomposingthemostparsimoniousexplanatory latewinterandlatesummerindicatethatS.alveolatareefspromote
model. Vectors represent the environmental parameters selected by the DistLM animportantbenthicprimaryproductionallyearround,thatcould
routine.Theblackdiamonds,thegreysquaresandthelightgreycirclesrepresentthe be a relevant food source for deposit- (Kanaya et al., 2008) and
engineered,theassociatedandthecontrolsedimentsamplesrespectively.
suspension-feeders (Lefebvre et al., 2009) through resuspension
processes(Hylleberg,1975;Ubertinietal.,2015).Intheassociated
definedas“submarineorexposedatlowtide,rockysubstratesand sediments,MPBoftengrowsonsmallaccumulationsofpuremud
biogenicconcretions”.Inthelightofourfindings,wecanverywell andisconsequentlyeasilyerodedandavailabletoconsumers.Such
considertheengineeredandtheassociatedsedimentsasthesame benthicprimaryproductionmayhaveatrophicimportanceduring
sediment but under two different forms, a consolidated (engi- thewintermonths(Lefebvreetal.,2009),whenthephytoplankton
neered sediments) and an unconsolidated form (associated sedi- productionistypicallylow(ArbachLeloupetal.,2008;Cugieretal.,
ments). Hence, we propose to widen the definition of a “reef” to 2010).FilterfeedingmollusksareknowntostimulateMPBgrowth
includethenon-engineeredsedimentsunderitsdirectinfluence. (Engeletal.,2017;Newelletal.,2002)viainorganicnutrientrelease
The main difference between the engineered and associated (i.e.carbon,nitrogenandphosphorus(vanBroekhovenetal.,2014))
sedimentsconcernstheirmudcontent.Atbothseasons,theengi- and bacterial remineralization of their biodeposits (van
neered sediments havea mean mudcontent around 10%, as pre- Broekhoven et al., 2015). Similarly, S. alveolata produces large
viouslyobservedbyLeCametal.(2011).Sabellariawilsoniveneers amountsoffecesandpseudofecesvisibleonthesediment(Dubois
havealsobeenreportedtopresentconsistentsiltandclaycontents et al., 2005), that could favor MPB growth. Primary production
across two contrasting seasons (rainy and dry seasons in Ataide could also be enhanced by the presence of other suspension-
et al., 2014) indicating that Sabellariidae polychaetes build new feeders living in the engineered sediments, such as Magallana
10 A.G.Jonesetal./Estuarine,CoastalandShelfScience200(2018)1e18
Table3
ResultsoftheManteltestsbetween(a)thedifferentbetadiversitymatricesandthemudcontentdistancematrixand(b)thedifferentabundance-baseddissimilaritymatrices
andthemudcontentdistancematrixatbothsamplingperiods(latewinterandlatesummer).bsoristheSørensenpairwisedissimilarityandaccountsforthetotalbetadi-
versity,bsimistheSimpsonpairwisedissimilarityandaccountsfortheturnovercomponentofthetotalbetadiversity,bnesisthenestedness-resultantdissimilarityandac-
countsforthenestednesscomponentofthetotalbetadiversity;bsor¼bsimþbnes.dBCistheBray-Curtisindexofdissimilarityandaccountsforthetotalabundance-based
dissimilarity,dBC-balisthebalancedvariationinabundancescomponentoftheBray-Curtisdissimilarityandisequivalenttoanabundance-basedturnover,dBC-graisthe
abundancegradientcomponentofBray-Curtisdissimilarityandisequivalenttoanabundance-basednestedness;dBC¼dBC-balþdBC-gra.Significantsimulatedp-values
(p<0.05)andassociatedobservedcorrelationareinbold.
Latewinter Latesummer
Observedcorrelationr Simulatedp-value Observedcorrelationr Simulatedp-value
(a)Betadiversityindices
bsor 0.13 0.070 0.24 <0.001
bsim 0.066 0.23 0.15 0.0066
bnes 0.032 0.33 0.077 0.094
(b)Abundance-baseddissimilarityindices
dBC 0.14 0.052 0.38 <0.001
dBC-bal 0.050 0.28 0.058 0.18
dBC-gra 0.046 0.28 0.29 <0.001
Fig.5. LatewinternMDSordinationplotsofthebenthicmacrofaunaassemblagesbasedona)theSørensentotalbetadiversity,b)thenestednesscomponentofthetotalbeta
diversity,c)theBray-Curtisindexofdissimilarityandd)theabundancegradientcomponentoftheBray-Curtisdissimilarity.ThestressvalueofthenMDSisindicatedoneachplot.
Thelinesindicatethedifferentfittedmudcontentsobtainedusingthe‘ordisurf’function.
gigas,whichcanreachdensitiesof100ind.m(cid:4)2asmeasuredinthe these pseudofeces are deposited on the associated sediments, it
disturbed engineered sediments using the quadrats. As already couldincreasetheirconcentrationinsolublecarbohydrates.Solu-
observedinFicopomatusenigmaticusreefs(Bruschettietal.,2011), ble carbohydrates also compose the extracellular polymeric sub-
S.alveolatareefsprobablyincreasethebentho-pelagiccouplingby stancesproducedbybenthicdiatoms(Bellingeretal.,2009)andare
linkingpelagicorganicmattertothebenthiccompartmentviatheir animportantsourceoforganiccarbon,rapidlyconsumedbyhet-
suspension-feedingactivityandbiodeposition. erotrophicmicroorganismspresentinthesediment(Bhaskarand
In late winter and late summer, associated sediments had Bhosle, 2005; Goto et al., 2001). Consequently, S. alveolata pres-
consistently higher soluble carbohydrate concentrations than the ence could support allyear round an important bacterial activity
controlsediments.Carbohydratesarethecomponentsofthemucus through the soluble carbohydrates excreted by the diatoms and
coating the pseudofeces produced by S. alveolata and other presentinthemucuscoatingthebiodeposits.Thisorganiccarbon
suspension-feeders (van Broekhoven et al., 2015). Hence, when can either be used by the bacteria for their growth (bacterial