Submitted 11 November 2016Accepted 31 December 2016Published 31 January 2017

Corresponding authorKyosuke Momotakyomomotagmailcom

Academic editorMagnus Johnson

Additional Information andDeclarations can be found onpage 16

DOI 107717peerj2952

Copyright2017 Momota and Nakaoka

Distributed underCreative Commons CC-BY 40

OPEN ACCESS

Influence of different types of sessileepibionts on the community structure ofmobile invertebrates in an eelgrass bedKyosuke Momota1 and Masahiro Nakaoka2

1Graduate School of Environmental Science Hokkaido University Akkeshi Hokkaido Japan2Akkeshi Marine Station Field Science Center for Northern Biosphere Hokkaido University AkkeshiHokkaido Japan

ABSTRACTEelgrass (Zostera marina) beds are known to have high ecological and economicalvalues within coastal ecosystems of the temperate northern hemisphere although theirbiodiversity and functions varied greatly from sites to sites The variation in the biomassabundance and diversity of mobile invertebrates in eelgrass beds has been examinedin relation to various abiotic and biotic factors such as water temperature salinityeelgrass biomass and epiphytic microalgae presence However the importance of sessileepibionts such as macroalgae and calcific spirorbid polychaetes attached to eelgrassblades has not been the focus of previous studies In the present study we examinedthe effects of three different sessile epibionts namely branched red algae filamentousgreen algae and calcific spirorbid polychaetes on the biomass and diversity of mobileinvertebrates in the eelgrass beds of Akkeshi in northeastern Japan The relationshipsbetween seven abiotic and biotic variables including three types of epibionts andbiomass of 11 dominant mobile invertebrate species as well as three community-levelvariables (the total biomass of mobile invertebrates species richness and the Shannon-Wiener species diversity index) were analyzed using a linear mixed model Our resultsshow that branched red algae are correlated with Pontogeneia rostrata Lacuna sppNereis sp Syllis sp and the total biomass of mobile invertebrates filamentous greenalgae with P rostrataAnsola angustata and the species diversity ofmobile invertebratesand spirorbid polychaetes withA angustata Lacuna spp Siphonacmea oblongata Syllissp the species richness and diversity of mobile invertebrates The effect size of theepibionts was similar or even higher than that of abiotic and eelgrass factors on thetotal biomass of mobile invertebrates species richness species diversity and mostof dominant invertebrate populations across the taxonomic groups Consequentlyepibiotic macroalgae and spirorbid polychaetes can be good predictors of the variationin the total biomass species richness and species diversity of mobile invertebrates andthe biomass of major dominant species especially for species that have a relatively highdependency on eelgrass blades These results suggest that the different functional groupsof sessile epibionts have significant roles in determining the biomass and diversity ofmobile invertebrates in eelgrass beds

Subjects Biodiversity Ecology Environmental Sciences Marine BiologyKeywords Zostera marina Spirorbid polychaetes Environmental gradient Linear mixed modelMacroalgae Community structure Epibiotic organisms Species diversity Biomass Marineinvertebrates

How to cite this article Momota and Nakaoka (2017) Influence of different types of sessile epibionts on the community structure of mo-bile invertebrates in an eelgrass bed PeerJ 5e2952 DOI 107717peerj2952

INTRODUCTIONThe abundance biomass and species diversity of marine benthic invertebrate communitiesvary greatly with multiple abioticbiotic factors The effects of temperature and salinityas environmental filters have been known to be critical factors that regulate populationcommunity patterns and processes in coastal habitats especially in estuaries where strongenvironmental gradients are generated by tidal fluctuation and freshwater inflow (egYsebaert et al 2003 Yamada et al 2007b Douglass et al 2010 Blake amp Duffy 2010)Water temperature can either increase or decrease the abundance and diversity ofcomponent species (eg Somero 2002 Harley et al 2006 Hoegh-Guldberg amp Bruno 2010Meager Schlacher amp Green 2011) whereas a decrease in salinity generally leads to a lowerspecies diversity and higher dominance by tolerant species (eg Ysebaert et al 2003Yamada et al 2007b) Marine plants act as both a food resource because plant resourceutilizers dominate in marine benthic invertebrate communities (eg Valentine amp Heck Jr1999 Harley 2006 Poore et al 2012) and as habitat-former (eg Attrill Strong amp Rowden2000 Lee Fong amp Wu 2001 Thomsen 2010 Gartner et al 2013)

Eelgrass (Zostera marina) is an important marine foundation species that is widelydistributed along the coast of the northern hemisphere (Hughes et al 2009) The complexphysical structures created by eelgrass provide a habitat for many organisms (JernakoffBrearley amp Nielsen 1996Heck Jr Hays amp Orth 2003) which leads to an enhanced biodiver-sity and secondary production (Hemminga amp Duarte 2000Duffy 2006Valentine amp Duffy2006) A benthic invertebrate community in the above-ground parts of seagrass bedsmainlyconsists of small crustaceans gastropod mollusks and polychaetes most of whichare herbivores and detritivores (Valentine amp Heck Jr 1999 Heck Jr et al 2000) Theseinvertebrates play an important role in mediating the energy flow in the eelgrass bedecosystem (Duffy amp Hay 2000Duffy Richardson amp France 2005) To explore plant-animalinteractions in eelgrass bed communities many studies have investigated the relationshipbetween animal abundance and various eelgrass traits such as biomass shoot density leaflength habitat patch structure and epiphytic microalgal (eg diatoms) biomass that serveas food resources (Attrill Strong amp Rowden 2000 Gartner et al 2013 Whalen Duffy ampGrace 2013) However large epibiotic organisms such as macroalgae and sessile animals(eg spirorbid polychaetes tunicates bryozoans hydrozoans) attached to eelgrass bladescan also affect the mobile invertebrate community through resource provisioning andorhabitat modification Despite some studies noting that the role of macroalgae on seagrassblades as a food resource or as a habitat provision can be one of the determinants of theabundance of mobile invertebrates (Valentine amp Duffy 2006 Gartner et al 2013 WhalenDuffy amp Grace 2013) most studies have focused only on the importance of seagrass andormicroalgae (eg Jernakoff Brearley amp Nielsen 1996 Heck Jr amp Valentine 2006) Whilstrelevant studies are few the sessile organisms such as invasive tunicates and juvenile bayscallops attaching on eelgrass blade can affect mobile invertebrates either by providingrefuge from predation (Long amp Grosholz 2015) or by becoming a food resource (Lefchecket al 2014) Interpreting variations in the mobile invertebrate community in relation tovarious functional groups of epibiotic organisms that differ in size morphology habitat

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 222

requirement and life history traits is thus necessary to deepen our understanding of theorganization of animal assemblages in eelgrass beds and of the influences these organismshave on each other and on eelgrass

An extensive eelgrass meadow consisting mostly of Zostera marina and partly ofZ japonica and Ruppia maritima is located in the Akkeshi-ko estuary and the AkkeshiBay in eastern Hokkaido Japan (Hasegawa Hori amp Mukai 2007) From early summer tolate fall a large variety of algae and sessile animals (epibiotic species) which attach toeelgrass blades are observed including microalgae branched red algae Neosiphoniasp Chondria dasyphylla filamentous green algae Cladophora sp calcareous algaePneophyllum zostericola and spirorbid polychaetes such as Neodexiospira brasiliensisbryozoans hydrozoans and tunicates Among them microalgae the branched red algaeand the spirorbid polychaetes are dominant in eelgrass beds for a long term betweenearly summer and late fall with the peak of abundance between August and September(Hamamoto amp Mukai 1999 Kasim ampMukai 2006 Hasegawa Hori amp Mukai 2007 KMomota 2013 unpublished data) Previous studies on benthic invertebrate assemblagesin the Akkeshi-ko estuary and Akkeshi Bay have focused on their variability in relation tothe salinity gradient (Yamada et al 2007a Yamada et al 2007b) In addition to salinitythe spatial heterogeneity of other abioticbiotic factors (eg water temperature microalgalbiomass and eelgrass biomass) is also high in estuarine systems such as the Akkeshi-ko estuary (Iizumi et al 1996 Kasim ampMukai 2006 Hasegawa Hori amp Mukai 2007)Nevertheless no previous study has investigated the mobile invertebrate communitystructure using an approach that simultaneously accounts for the details of sessile epibiontsand environmental control by abiotic factors in the seagrass beds in Akkeshi

In the present study we investigated how multiple abiotic and biotic factors are relatedto the variation in the community structure (total mobile invertebrate biomass speciesrichness and species diversity) of the mobile invertebrates and the population biomass ofthe dominant species in the eelgrass beds in Akkeshi Our specific focus was to test therelationship between various sessile epibionts on eelgrass blades and the mobile inverte-brates that live on eelgrass blades Including these factors in the multivariate model thisanalysis expands the classical models that consider only abiotic factors eelgrass andmicroalgae as the explanatory variables

MATERIALS AND METHODSStudy areaThe Akkeshi-ko estuary (locally called Akkeshi Lake) and Akkeshi Bay are located in North-eastern Hokkaido Japan (Fig 1) and are connected to each other through a narrow channel(width approximately 500 m depth approximately 10 m) The Akkeshi-ko is a brackishestuary shallow water (depth range in most of the lake 08ndash17 m with the maximum dif-ference in tide levels of up to approximatelyplusmn06m) with an area of approximately 32 km2Most bottom areas of the Akkeshi-ko estuary are muddy and covered with eelgrass (Zosteramarina) except for the aquaculture farms of the clam Venerupis philippinarum in theintertidal zone near the channel (Kasim ampMukai 2006 Hasegawa Hori amp Mukai 2007

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 322

Figure 1 Location of the study sites in the Akkeshi-ko estuary and the Akkeshi Bay in NortheasternJapan The area enclosed by a dashed circle is the Akkeshi-ko estuary Most of the clam aquaculturegrounds are located in the western part of the estuary (indicated by a dotted circle)

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 422

Yamada et al 2007a Yamada et al 2007b) Here freshwater input from the BekanbeushiRiver which accounts for 988 of all of the flow volume (Iizumi et al 1996) and tidalseawater input from the Akkeshi Bay cause steep physical and chemical environmentalgradients (Iizumi et al 1996 Yamada et al 2007a)

Akkeshi Bay has an area of approximately 110 km2 and opens to the Pacific Oceanat the south end Two seagrass species Z marina and Z asiatica are present from theintertidal zone to the subtidal zone (5 m below mean low water) the former occurs atdepths shallower than 2 m and the latter dominates in deeper water (Watanabe Nakaoka ampMukai 2005) The influence of the freshwater discharge on species composition of seagrasscommunity is observed near the channel connecting the bay to the Akkeshi-ko estuary(Yamada et al 2007a)

In this study we established stations in the Akkeshi-ko estuary (BK river mouth ofthe Bekanbeushi River HN Horonitai TB Toubai SL the southern lake CL the centrallake and CK Chikarakotan) and one station in Akkeshi Bay (SR Shinryu) (Fig 1) BK(mean sea level MSL hereafter 09 m) is located at the mouth of the Bekanbeushi Riverand is strongly affected by freshwater inflow The vegetation is dense with small-sizedZ marina (average shoot length of 10 m in August) HN (MSL 11 m) is in a location witha high water temperature and medium salinity relative to the other stations In additionto Z marina Ruppia maritima a seagrass species that is more tolerant to low-saline wateroccurs at HN The eelgrass beds at HN are mostly continuous but have some gaps andthe average shoot length in August is 13 m TB (MSL 11 m) and SL (MSL 10 m) have arelatively low salinity compared to that of the other stations and are the furthest stationsfrom the Akkeshi Bay Although these two stations are in a similar environment the wateris often more turbid and the eelgrass bed is patchier at TB than SL SL has a higher seagrassbiomass and shoot density than TB The average shoot length of eelgrass is approximately13 m in August at both of these stations CL (MSL 14 m) and CK (MSL 15 m) aredeeper stations with a higher salinity and are dominated by longer eelgrass (shoot length15ndash35 m at the peak season) The eelgrass at SR (MSL 15 m) in the Akkeshi Bay has asimilar shoot size to that in CL and CK Here the dominant seagrass species changes fromZ marina bed to Z asiatica at a depth of approximately 2 m as mentioned above

According to Yamada et al (2007a) salinity varies significantly among stations butdoes not vary greatly among seasons During the summer (from July to August) eelgrassbiomass microalgal biomass and mobile invertebrates reach their peak (Hasegawa Horiamp Mukai 2007 Yamada et al 2007b) Seasonal changes in the mobile invertebrate speciesrichness are not clearly understood (Yamada et al 2007b)

Field samplingWe conducted a field survey in August 2012 Sample collection was performed when thetidal current was slow We collected mobile invertebrates on eelgrass blades when the waterlevel was deeper than the average sheath length of the eelgrass at each station (BK 20 cmHN TB SL 30 cm CL CK SR 40 cm) Because the eelgrass at our study stations is tall(gt1 m) compared to the average water depth of each station the canopy usually reaches thewater surface (except for at extremely high tides) All samplings were performed under these

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conditions We targeted mobile invertebrates but excluded some species with remarkablyhigh mobility and low dependency on eelgrass habitat such as mysids and decapods(Yamada et al 2007b) which were not quantitatively collected by our method (see below)

Wemeasured water temperature and salinity once at each station using amemory sensor(AAQ-175 RINKO JFE Advantech Co Ltd Japan) To obtain the representative valuesthe sensor was carefully placed approximately 50 cm from the bottom to accurately reflectthe environment inside of the seagrass meadow

We collected three replicate samples (a total of 21 samples from all stations) of mobileinvertebrates spirorbid polychaetes and epiphytic macroalgae together with the entireabove-ground parts of the eelgrass using a mesh bag (bore diameter 20 cm mesh size 01mm) based on the mouth area of the mesh bag (314 cm2) Upon collection we counted thenumber of eelgrass shoots to determine shoot density Formicroalgae five replicate sampleswere collected per station using separate plastic zip bags for each eelgrass shoot becausemicroalgae easily fell off from eelgrass blades when collected with the mesh bag

Laboratory proceduresImmediately after being transported to the laboratory the microalgae were scraped fromthe eelgrass blades using a glass slide separated from other organisms such as macroalgaeand spirorbid polychaetes and then filtered using glass fiber filters (Whatman GFF filterϕ 47 mm Whatman International Ltd Maidstone UK) If other organisms were presentin the microalgal samples we carefully removed them from the filters with forceps Otherepibiotic organisms collected using mesh bags were separated from the eelgrass by scrapingthem off with a glass slide these organisms were classified as red algae green algae spirorbidpolychaetes and mobile invertebrates To obtain dry mass eelgrass shoots red algae greenalgae spirorbid polychaetes and filtered microalgae were dried at 60 C for 4 days in smallaluminum foil bags and then weighed We counted and identified the mobile invertebratesafter extraction with a sieve (500 microm) and fixation with 70 ethanol Identification ofmobile invertebrates was made to the lowest taxonomical unit possible (mostly to species)using detailed guides from the literature (Gammarid amphipod Nishimura 1995 Carlton2007 Caprella amphipod Isopod Copepod Cumacea Nishimura 1995 Carlton 2007Gastropod Okutani 2000 Polychaeta Nishimura 1992 Imajima 1996 Imajima 2001Turbellaria Nishimura 1992 Carlton 2007 Hirunoidea Nishimura 1992) and the WorldRegister of Marine Species online database (WoRMS httpwwwmarinespeciesorg)

Statistical analysisWe used as predictors two abiotic factors (water temperature and salinity) and six bioticfactors (eelgrass biomass (g dry weight per unit area g DW mminus2) eelgrass shoot density(shoots mminus2) microalgal biomass (g DW mminus2) red algal biomass (g DW mminus2) greenalgal biomass (g DW mminus2) and spirorbid polychaete biomass (g DW mminus2)) For eelgrassbiomass we used the dryweight data collected usingmesh bags Becausemicroalgal biomasswas collected by a different sampling procedure from other biotic variables we usedthe mean value of five replicates In this study one of our interests was the effects ofmorphological traits of macroalgae and spirorbid polychaetes Thus we separated red and

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 622

green algae by a morphological trait (red algae branched green algae filamentous) Allinvertebrate biomass (mg ash-free dry weight per unit area mg AFDWmminus2) was estimatedfrom the abundance and the size fraction using the empirical equations in Edgar (1990)

To test which of the eight bioticabiotic factors was a likely predictor of the variation inthemobile invertebrate community we fitted linearmixedmodels (LMMs) with a Gaussiandistribution (Bolker et al 2009) The station was used as a random variable As responsevariables we used the biomass of 11 dominant species for the population-level analyses andtotal invertebrate biomass species richness and species diversity (Shannon-Wiener diversityindex calculated based on biomass data) for community-level analyses The 11 mostdominant species were selected by a threshold whereby the biomass proportion accountedfor more than 1 of the total invertebrate biomass (see Table S1) Ostreobdella kakibir(Hirudinea) was omitted from the analysis because it occurred only at one station (SR)even though they satisfied the requirement R software (version 313) was used for all ofthe analyses (R Development Core Team 2015)

Prior to the LMM fit all of the variables excluding species diversity were square roottransformed to improve homoscedasticity and meet the assumptions of normality of theLMMs after checking for normality with the ShapirondashWilk test To test for collinearitybetween the eight environmental variables we calculated Pearsonrsquos correlation coefficientsfor all pairs If the absolute value of the coefficient (r) was greater than 07 the level wherecollinearity does not affect model predictions (Dormann et al 2013) we removed therelevant predictor as necessary Because water temperature and microalgal biomass werehighly correlated (Pearsonrsquos r =minus082 P lt 001) we removed microalgal biomass fromthe models After this removal we tested potential multicollinearity among the remainingpredictors using the variance inflation factor (VIF) analysis with a cutoff of 10 (egDormann et al 2013) VIF values were calculated using the vifmer function developedby Frank (httpsrawgithubusercontentcomaufrankR-hacksmastermer-utilsR)However all seven predictors were below the VIF value of 10 and remained We thereforedefined a reduced model with the seven predictors as the full model

We fitted the LMMs using the lmer function in the lme4 package (Bates et al 2014)To obtain P-values of the LMMs we used the lmerTest package (Kuznetsova Brockhoff ampChristensen 2014) We selected the optimal model comparing the candidate models on allcombinations of the predictors by theAkaike information criterion as corrected for the smallsample size (AICc Burnham amp Anderson 2002) We obtained AICc based on the maximumlikelihood (ML) for comparisons among the LMMs because the restricted maximumlikelihood (REML) is inappropriate in the case when the fixed structure is differentbetween the candidate models (Zuur et al 2009) but the parameters were estimated byREML We used the AIC c tab function in the bbmle library (Bolker amp R DevelopmentCore Team 2013) to compare the AICc After setting the optimal models we obtainedthe standardized coefficients as effect sizes by re-fitting using standardized variablesthat were scaled by the sample standard deviation and centered by sample mean values

Additionally when the effect of water temperature was detected we tested therelationship between mobile invertebrates and microalgal biomass which was omittedfrom the LMM because of the multi-collinearity with water temperature

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Table 1 Environmental conditions at seven stations in the Akkeshi-ko estuary and Akkeshi Bay Abiotic factors in this study are indicated byboldface For water temperature and salinity we also presented data in August reported by the other studies

Factors Stations Ref

BK HN TB SL CL CK SR

AbioticWater temperature ( C) 238 261 259 255 210 226 225 a

214 224 229 ndash 225 200 188 b

181 203 203 210 185 173 166 c

217 241 238 239 219 227 188 d

Salinity 250 264 270 271 292 263 299 a

168 281 284 ndash 296 320 286 b

161 ndash ndash 239 260 265 296 e

267 250 136 224 274 284 299 c

212 236 260 262 268 267 299 d

BioticEelgrass factorDry mass (g mminus2) Mean 1522 1404 1195 2163 2168 1903 2779 a

SD 258 373 308 309 268 650 685Shoot density (mminus2) Mean 2337 853 747 1590 853 853 960 a

SD 185 185 185 185 00 185 185

Epibiont dry massMicroalgae (g mminus2) Mean 732 256 779 192 3845 1134 763 a

SD 639 65 466 50 1198 589 262Red algae (g mminus2) Mean 01 90 00 41 00 46 00 a

SD 01 60 ndash 22 00 76 ndashGreen algae (g mminus2) Mean 75 00 00 82 280 01 00 a

SD 74 ndash ndash 43 162 00 ndashSpirorbid shell (g mminus2) Mean 535 218 68 00 00 19 9443 a

SD 280 187 76 ndash ndash 32 1906

NotesaThis studybIizumi et al (1996)cMNakaoka et al (2010 unpublished data)dKMomota (2013 unpublished data)eKasim ampMukai (2006)

RESULTSEnvironmental factorsWater temperature was lower at the four stations (BK CL CK and SR) near the channelthan at the other three stations in the inner parts of the estuary (HN TB and SL) (Table 1)Salinity was lower at the lake-side stations (BK HN TB SL and CK) that were influencedby freshwater inputs For these stations the inter-annual variation was also higher as shownby data collected by ourselves and other studies (Table 1)

Eelgrass biomass varied between 140 and 278 g DW mminus2 among the stations It waslowest at TB followed by HN and BK (Table 1) Eelgrass shoot density ranged between 85and 234 shoot mminus2 It was highest at BK and second highest at SL The mean densities were

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not largely different among other stations Microalgal biomass varied bymore than ten-foldbetween the lowest station (SL) and the highest station (CL) In the latter the microalgalbiomass exceeded the biomass of the eelgrass Macroalgae were not present at TB andSR Branched red algae were dominated by Neosiphonia sp and Chondria dasyphylla andfilamentous green algae were dominated by Cladophora sp The mean biomass of red algaewas highest at HN and that of green algae was highest at CL though their biomasses wereless than 15 of that of eelgrass Spirorbid polychaetes were not present at SL and CLThey were highly abundant at SR where their biomass was more than three-fold greaterthan the eelgrass biomass

Mobile invertebrate communityA total of 32 mobile invertebrate species were collected in this study (Table S1) At taxo-nomic levels polychaete wormsmade up 322of the total biomass followed by gastropods(313) gammarid amphipods (230) and isopods (88) At the species level a poly-chaeteNereis sp was most dominant (246) followed by gastropods Lacuna spp (234)and the gammarid amphipod Ampithoe lacertosa (180) For an additional eight speciesincluding two gammarid amphipods (Monocorophium spp and Pontogeneia rostrata) twoisopods (Cymodoce japonica and Paranthura japonica) two gastropods (Ansola angustataand Siphonacmea oblongata) and two polychaetes (Exogone naidina and Syllis sp) theirproportions were less than 5 at most

Themean value of the total mobile invertebrate biomass was the highest at CK andmuchlower at stations along the coastline (HN TB and SL) Species richness was the highest atCL followed by CK and was approximately the same level at the other stations (Fig 2)The mean value of species diversity was the highest at CL and the lowest at SR (Fig 2)

Population level analysesWe found that each of the nine invertebrate populations belonging to gammaridagastropoda and polychaeta was predicted by a different combination of environmentalfactors in the optimal models (Table 2) The effect size of three epibionts on dominantinvertebrate species was either similar or larger than abiotic and eelgrass factors (Fig 3)For two isopods no environmental factor correlated with their biomass

Water temperature was selected as the responsible factor for the variation of A lacertosaLacuna spp and all three polychaetes Among them only Syllis sp showed a significantcorrelation (positive) The significant effect of the salinity gradient was detected for Aangustata (negative) and S oblongata (positive)

For the two predictors relevant to the characteristics of the eelgrass bed the above-ground biomass showed a significant positive relationship only with Syllis sp whereasshoot density was significantly correlated with Monocorophium spp (positive) P rostrata(negative) and E naidina (negative) (Table 2)

The biomasses of sessile epibionts (red algae green algae and spirorbid polychaetes) oneelgrass blades were correlated with many invertebrate populations in different mannersexcluding A lacertosaMonocorophium spp two isopods and E naidina Red algal biomasswas positively correlated with P rostrata Lacuna spp and Nereis sp but negatively corre-lated with Syllis sp and tended to be negatively correlated with A angustata Green algal

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Figure 2 (A) The total invertebrate biomass (B) species richness and (C) Shannon-Wiener diversityindex at the seven stations in the Akkeshi-ko estuary and Akkeshi Bay The bars indicate the mean valueswith SDs The order of the stations is lined up based on relative size of the impact of freshwater inflow orseawater from Akkeshi Bay

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Table 2 Results of LMMs for explaining responsible environmental factors on variation in mobile invertebrate populations and communitycomponents AICc scores and delta AICc are also reported Significant coefficients (P-values lt 005 level) and the lowest AICc scores are in boldface

Response Model Predictor AICc 1AICc

(Intercept) WT Sal ZMbm ZMden Redalg Grnalg SPbm

PopulationGammarid amphipodaAmpithoelacertosa

Null 33978 ndash ndash ndash ndash ndash ndash ndash 1939 10

Full 673282 minus87465 minus48498 minus0482 4427 7243 minus0761 minus0736 2167 238Optimal 1097930 minus79180 minus129700 1929 ndash

Monocorophiumspp

Null 8669 ndash ndash ndash ndash ndash ndash ndash 1377 20

Full 582409 minus42288 minus72767 0079 0986 0265 0428 0059 1601 244Optimal minus6824 1469 1357 ndash

Pontogeneiarostrata

Null 10068 ndash ndash ndash ndash ndash ndash ndash 1472 198

Full 247381 minus11576 minus32023 0407 minus2751 4934 2878 0111 1395 121

Optimal 20728 minus1842 5023 2523 1274 ndash

IsopodaCymodocejaponica

Null 11630 ndash ndash ndash ndash ndash ndash ndash 1870 00

Full 605245 minus15501 minus100306 4532 minus5585 0308 2552 minus0113 2111 241Optimal 11630 1870 ndash

Paranthurajaponica

Null 14077 ndash ndash ndash ndash ndash ndash ndash 1734 00

Full 132132 8691 minus32148 0349 minus0924 2623 4411 0463 2000 266Optimal 14077 1734 ndash

GastropodaAnsola angus-tata

Null 6014 ndash ndash ndash ndash ndash ndash ndash 1596 101

Full 555710 minus12507 minus96596 minus0524 1180 minus1487 3730 0923 1673 178Optimal 600167 minus116259 minus2645 5102 1149 1495 ndash

Lacuna spp Null 28820 ndash ndash ndash ndash ndash ndash ndash 1970 112Full 880106 minus129988 minus43910 0940 minus2094 10442 minus2761 2607 2039 181

Optimal 522161 minus106591 10634 2696 1858 ndash

Siphonacmeaoblongata

Null 8003 ndash ndash ndash ndash ndash ndash ndash 1666 172

Full minus350288 minus16668 82450 minus1654 2567 1664 minus2471 1063 1727 233Optimal minus190996 36374 1426 1494 ndash

(continued on next page)

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Table 2 (continued)

Response Model Predictor AICc 1AICc

(Intercept) WT Sal ZMbm ZMden Redalg Grnalg SPbm

PolychaetaExogonenaidina

Null 8274 ndash ndash ndash ndash ndash ndash ndash 1821 gt01

Full 1003724 minus66607 minus119185 1236 minus5958 minus1510 0675 minus0184 2034 213Optimal 988365 minus75725 minus106916 minus4922 1821 ndash

Nereis sp Null 23110 ndash ndash ndash ndash ndash ndash ndash 2117 64Full 1994677 minus171788 minus216463 5651 minus9760 13928 7192 0017 2211 158

Optimal 844824 minus171482 16967 2053 ndash

Syllis sp Null 6678 ndash ndash ndash ndash ndash ndash ndash 1752 13Full minus342880 45302 14699 5108 minus0141 -6889 minus1247 minus1140 1915 176Optimal minus269866 45615 4886 minus6616 minus0908 1739 ndash

Community componentTotal inverte-brate biomass

Null 2785 ndash ndash ndash ndash ndash ndash ndash 720 103

Full 60096 minus5936 minus5985 0214 minus0097 0456 0184 0056 810 193Optimal 23569 minus4937 0219 0401 617 ndash

Speciesrichness

Null 3027 ndash ndash ndash ndash ndash ndash ndash 280 147

Full 16581 minus1485 minus1211 0080 minus0094 minus0036 0080 minus0023 336 203Optimal 13909 minus2185 minus0031 133 ndash

Speciesdiversity

Null 1255 ndash ndash ndash ndash ndash ndash ndash 199 86

Full 2056 minus0126 minus0049 0010 0012 minus0068 0034 minus0026 367 254Optimal 1288 0065 minus0020 113 ndash

NotesWT water temperature Sal salinity ZMbm eelgrass biomass ZMden eelgrass shoot density Redalg red algal biomass Grnalg green algal biomass SPbm spirorbidpolychaete biomass

biomasses were positively correlated with P rostrata and Lacuna spp The biomass ofspirorbid polychaetes was positively correlated with all three species of gastropods and wasnegatively correlated with Syllis sp

Although epiphytic microalgae were removed from our analysis because of the collinear-ity with water temperature no significant correlation was found for species that werecorrelated with water temperature (A lacertosa Pearsonrsquos r = 405 P = 025 Lacuna sppr =minus342 P = 069 E naidina r = 031 P = 092 Nereis sp r = 1087 P = 034 Syllissp r = 021 P = 086)

Community level analysesThe total invertebrate biomass tended to decrease with water temperature and significantlyincreased with increasing eelgrass biomass and red algal biomass (Table 2) Species

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Figure 3 Effect size of abiotic and biotic factors onmobile invertebrate populations and communitydetected by linear mixedmodelsWater temperature (WT) salinity (Sal) eelgrass biomass (ZMbm) eel-grass shoot density (ZMden) branched red algae (Redalg) filamentous green algae (Grnalg) and spiror-bid polychaetes (SPbm) We only reported the results of predictors selected by the best models (Table 2)Open circles represent detected predictors without significance (P gt 005) and filled circles represent de-tected predictors with significance (P lt 005) Error bars indicate standard errors of effect sizes

richness showed a negative correlation with water temperature and spirorbid polychaetesSpecies diversity was positively correlated with green algal biomass but was negativelycorrelated with spirorbid polychaetes (Table 2) The effect size of red algal biomass on thetotal invertebrate biomass was similar to that of eelgrass biomass and that of spirorbidpolychaetes on species richness was also similar to that of water temperature (Fig 3)

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 1322

DISCUSSIONThe present study demonstrated that the biomass gradient of epibiotic organisms (egmacroalgae and spirorbid polychaetes) was a good predictor of the variation in some domi-nant mobile invertebrates in the eelgrass bed and the population biomass of the communityparameters such as total biomass and diversity Further we found that the populationbiomasses and community components were not always influenced only by a single factorbut also by multiple factors The effect of the macroalgae is notable because these sessileepibionts have much lower biomass compared to the biomass of eelgrass and epiphyticmicroalgae However the observed relationships between these functional groups andmobile invertebrate populations varied greatly among the species

In the optimal models the effects of biomass of epibiotic organisms on the gammaridamphipod P rostrata all three gastropod species (A angustata Lacuna sp and S oblongata)and two polychaetes (Nereis sp and Syllis sp) were detected For those species the sessileepibionts were positively related to mobile invertebrate biomasses except for Syllis sp andP rostrata which showed a positive correlation with both red and green algae The algae areconsidered to be used as a temporal shelter (habitat) rather than as a food resource becausethese animals do not firmly attach to the eelgrass blades but rather drift among shoots(Suh amp Yu 1997 Yamada et al 2007b Yu Jeong amp Suh 2008) and because they have apreference for feeding on phytoplankton and detritus (Yu amp Suh 2011) High predationrisk for swimming amphipods with low self-defense abilities such as P rostrata hasbeen reported in several studies (Sudo amp Azeta 1992 Beare amp Moore 1998) In factgammarid amphipods are a major source of prey for blennoid fish in the eelgrass beds ofNorthern Japan (Watanabe et al 1996 Sawamura 1999 Yamada et al 2010) Thereforethe complex micro-habitat created by macroalgae allows them to escape these predators

All three gastropods increased in correlation with spirorbid polychaetes whereas theresponses to the other factors were different (Table 2) Because the gastropods adhere toflat seagrass blades the flat (simple) structure created by seagrass blades can be better thanthe rough structure of spirorbid polychaetes Therefore competition for space (negativeeffect) appears to be more expected than facilitation Although we do not have a goodanswer for the positive relationships one possibility for this unexpected result is that therough structure acts as a shelter because small-sized individuals (lt3 mm) are frequentin gastropod populations during the summer season (A angustata Momota personalobservation Lacuna spp Kanamori Goshima amp Mukai 2004 S oblongata ToyoharaNakaoka amp Tsuchida 2001)

Red algae are considered to positively affectNereis sp by providing habitat because poly-chaetes build tubes both on eelgrass blades and in red algal canopies in Akkeshi (Momotaunpublished data) The negative effect of red algae and spirorbid polychaetes on Syllis spmay suggest that this mobile polychaete prefers a simple structured habitat without acomplex micro-habitat created by eelgrass blades with sessile epibionts

In addition to the effects of sessile epibionts the significant effects of water temperaturesalinity eelgrass biomass and shoot density were detected for a majority of the dominantspecies although the patterns and directions of the effects were different among them

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 1422

Surprisingly eelgrass biomass was not correlated with most species except for Syllis spand the direction (positivenegative) of the effect of eelgrass shoot density was differentamong the species The same response of syllid polychaetes was reported in previousstudies (eg Bone amp San Martiacuten 2003) For eelgrass shoot density the result suggests thatit indirectly affects mobile invertebrates through interfering with multiple physical andbiological processes (eg water current and flux detritus and drifting algae trappingrecruitment and predation intensity Gambi Nowell amp Jumars 1990 Robbins amp Bell 1994Attrill Strong amp Rowden 2000 Bostroumlm amp Bonsdorff 2000 Lee Fong amp Wu 2001 Hovel etal 2002) Notably the contrasting relationships of P rostrata with eelgrass shoot densityand macroalgae imply that the shelter effect is different depending on the spatial scale (ieblade scale shootpatch scale)

The isopods C japonica and P japonica were not correlated with any abiotic or bioticfactors because of the low dependency on the seagrass habitat they can utilize other numer-ous habitats created by both natural and artificial materials (eg mussel beds oyster reefsMarchini et al 2014 Nakamachi Ishida amp Hirohashi 2015 gravel litter layer of macro-phytes Sargassum meadow Momota personal observation) Additionally their uniformappearance throughout all of the stations indicates that they have awide tolerance to a broadrange of environmental stress which leads to a lack of correlation with any of the abioticfactors Additionally the gammarid amphipod A lacertosa was not significantly correlatedwith any factors This species is widely distributed along the Pacific-rim coast of the northernhemisphere and utilizes a variety of plant habitats by building tubes (Hiebert 2015) whichmay explain why it did not show any relationship with the environmental gradients

Although the discussion on underlying drivers that generate apparent correlations (iethe causalities) between epibionts and mobile invertebrates is not our main focus theindirect effects and the top-down control of mobile invertebrates should also be taken intoaccount to interpret present findings For example we can give an alternative possibilityfor the positive relationship between gastropods and spirorbid polychaetes such that highgrazing of the gastropods facilitates the recruitment of spirorbid polychaetes through theremoval of the microalgal cover

Total biomass species richness and species diversity were differentially correlated withabioticbiotic factors and varied in a complex manner although processes were unclearThe optimal model of the three community variables contains one or two variables ofsessile epibionts The positive correlation of red algae with total biomass reflects that withhighly dominant species such as Lacuna spp and Nereis sp which occupied more than48 of the total biomass The negative interaction of spirorbid polychaetes with speciesrichness and diversity suggest that spirorbid polychaetes can decrease the homogeneity ofthe biomasses of component species within a community by allowing some competitivespecies to dominate The effect of green algae was found only on species evenness but not ontotal biomass nor on species richness suggesting that the green algae may increase speciesevenness by decreasing abundance of dominant species though the actual mechanismsremain to be cleared

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 1522

CONCLUSIONSThe present study suggests that macroalgae and sessile animals on eelgrass blades can affectthe biomass and diversity of mobile invertebrates and that incorporating these biotic factorscan improve the prediction of the variability of the mobile invertebrate community in theeelgrass bed However the underlying causal relationships appear to be complex and varygreatly from species to species Our findings were based on data collected over one samplingperiodwhen the eelgrass bedwasmost productive andwhen the abundance andor diversityof algae andmobile invertebrates typically reached their maximum Amore comprehensiveinvestigation of the functional relationships among the various types of organisms and ofthe temporal changes should be conducted in future studies on eelgrass bed communities

Recent studies demonstrated that the capacity for resistance and resilience toenvironmental stress and perturbations vary with food web structure in seagrass bedswhich knowledge can contribute to improvement of coastal management (Unsworth etal 2015 Maxwell et al 2016 Oumlstman et al 2016) Our study comparing population andcommunity level responses of epifauna to different types of epibionts on eelgrass blades addsmore knowledge on the complex trophicnon-trophic interactions of eelgrass communitiesand will promote more understandings of the resilience and the feedback mechanisms ofseagrass ecosystems which offer variable ecosystem services to human such as seafood pro-visioning and water quality controls (Cullen-Unsworth et al 2014 Nordlund et al 2016)

ACKNOWLEDGEMENTSWe wish to thank S Hamano H Katsuragawa and other members in Akkeshi MarineStation NM Kollars in UC Davis Dr K Abe and other staff in National Research Instituteof Fisheries and Environment of Inland Sea and T Maezawa in Hokkaido University

ADDITIONAL INFORMATION AND DECLARATIONS

FundingThis study is partly supported by JSTCREST (Establishment of core technology for thepreservation and regeneration of marine biodiversity and ecosystems) by JSPSKAKENHI(no 21241055) and by the Environment Research and Technology Development Fund(S-15 Predicting and Assessing Natural Capital and Ecosystem Services (PANCES)) ofthe Ministry of the Environment Japan The funders had no role in study design datacollection and analysis decision to publish or preparation of the manuscript

Grant DisclosuresThe following grant information was disclosed by the authorsJSTCRESTJSPSKAKENHI 21241055Environment Research and Technology Development Fund

Competing InterestsThe authors declare there are no competing interests

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 1622

Author Contributionsbull Kyosuke Momota conceived and designed the experiments performed the experimentsanalyzed the data contributed reagentsmaterialsanalysis tools wrote the paperprepared figures andor tablesbull Masahiro Nakaoka conceived and designed the experiments analyzed the datacontributed reagentsmaterialsanalysis tools wrote the paper

Data AvailabilityThe following information was supplied regarding data availability

The raw data has been supplied as Data S1

Supplemental InformationSupplemental information for this article can be found online at httpdxdoiorg107717peerj2952supplemental-information

REFERENCESAttrill MJ Strong JA Rowden AA 2000 Are macroinvertebrate communities influenced

by seagrass structural complexity Ecography 23114ndash121DOI 101111j1600-05872000tb00266x

Bates D Maechler M Bolker BWalker S 2014 lme4 linear mixed-effects models usingEigen and S4 Available at httpCRANR-projectorgpackage=lme4

Beare DJ Moore PG 1998 Aspects of the life histories of Perioculodes longimanusPontocrates arcticus and Synchelidium maculatum (Crustacea Amphipoda) atMillport Scotland Journal of the Marine Biological Association of the United Kingdom78193ndash209 DOI 101017S0025315400040029

Blake RE Duffy JE 2010 Grazer diversity affects resistance to multiple stressors in an ex-perimental seagrass ecosystem Oikos 1191625ndash1635DOI 101111j1600-0706201018419x

Bolker BM Brooks ME Clark CJ Geange SW Poulsen JR Stevens MHHWhite JSS2009 Generalized linear mixed models a practical guide for ecology and evolutionTrends in Ecology and Evolution 24127ndash135 DOI 101016jtree200810008

Bolker BM R Development Core Team 2013 bbmle tools for general maximumlikelihood estimation Available at httpCRANR-projectorgpackage=bbmle

Bone D SanMartiacuten G 2003 Ecological aspects of syllids (Annelida PolychaetaSyllidae) on Thalassia testudinum beds in Venezuela Hydrobiologia 496289ndash298DOI 101023A1026117503709

Bostroumlm C Bonsdorff E 2000 Zoobenthic community establishment and habitatcomplexitymdashthe importance of seagrass shoot-density morphology and physicaldisturbance for faunal recruitmentMarine Ecology Progress Series 205123ndash138DOI 103354meps205123

BurnhamKP Anderson DR 2002Model selection and multimodel inference a practicalinformation-theoretic approach New York Springer

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 1722

Carlton JT (ed) 2007 The light and Smith manual intertidal invertebrates from CentralCalifornia to Oregon 4th edition Berkeley University of California Press

Cullen-Unsworth LC Nordlund LM Paddock J Baker S McKenzie LJ Unsworth RKF2014 Seagrass meadows globally as a coupled socialndashecological system implicationsfor human wellbeingMarine Pollution Bulletin 83387ndash397DOI 101016jmarpolbul201306001

Dormann CF Elith J Bacher S Buchmann C Carl G Carreacute G Marqueacutez JRG GruberB Lafourcade B Leitatildeo PJ Muumlnkemuumlller T Mcclean C Osborne PE ReinekingB Schroumlder B Skidmore AK Zurell D Lautenbach S 2013 Collinearity a reviewof methods to deal with it and a simulation study evaluating their performanceEcography 3627ndash46 DOI 101111j1600-0587201207348x

Douglass JG France KE Richardson JP Duffy JE 2010 Seasonal and interannualchange in a Chesapeake Bay eelgrass community insights into biotic and abioticcontrol of community structure Limnology and Oceanography 551499ndash1520DOI 104319lo20105541499

Duffy JE 2006 Biodiversity and the functioning of seagrass ecosystemsMarine EcologyProgress Series 311233ndash250 DOI 103354meps311233

Duffy JE HayME 2000 Strong impacts of grazing amphipods on the organization of abenthic community Ecological Monographs 70237ndash263DOI 1018900012-9615(2000)070[0237SIOGAO]20CO2

Duffy JE Richardson JP France KE 2005 Ecosystem consequences of diversitydepend on food chain length in estuarine vegetation Ecology Letters 8301ndash309DOI 101111j1461-0248200500725x

Edgar GJ 1990 The use of the size structure of benthic macrofaunal communities toestimate faunal biomass and secondary production Journal of Experimental MarineBiology and Ecology 137195ndash214 DOI 1010160022-0981(90)90185-F

GambiMC Nowell ARM Jumars PA 1990 Flume observations on flow dynamicsin Zostera marina (eelgrass) bedsMarine Ecology Progress Series 61159ndash169DOI 103354meps061159

Gartner A Tuya F Lavery PS McMahon K 2013Habitat preferences of macroinverte-brate fauna among seagrasses with varying structural forms Journal of ExperimentalMarine Biology and Ecology 439143ndash151 DOI 101016jjembe201211009

Hamamoto K Mukai H 1999 Effects of larval settlement and post-settlement mortalityon the distribution pattern and abundance of the spirorbid tube worm Neodex-iospira brasiliensis (Grube) (Polychaeta) living on seagrass leavesMarine Ecology20251ndash272 DOI 101046j1439-048519992034075x

Harley CDG 2006 Effects of physical ecosystem engineering and herbivory onintertidal community structureMarine Ecology Progress Series 31729ndash39DOI 103354meps317029

Harley CDG Hughes AR Hulgren KMMiner BG Sorte CJB Thornber CS RodriguezLF Tomanek LWilliams SL 2006 The impacts of climate change in coastal marinesystems Ecology Letters 9228ndash241 DOI 101111j1461-0248200500871x

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 1822

Hasegawa N Hori M Mukai H 2007 Seasonal shifts in seagrass bed primary producersin a cold-temperate estuary dynamics of eelgrass Zostera marina and associatedepiphytic algae Aquatic Botany 86337ndash345 DOI 101016jaquabot200612002

Heck Jr KL Hays G Orth RJ 2003 Critical evaluation of nursery hypothesis forseagrassesMarine Ecology Progress Series 253123ndash136 DOI 103354meps253123

Heck Jr KL Pennock JR Valentine JF Coen LD Sklenar SA 2000 Effects ofnutrient enrichment and small predator density on seagrass ecosystemsan experimental assessment Limnology and Oceanography 451041ndash1057DOI 104319lo20004551041

Heck Jr KL Valentine JF 2006 Plantndashherbivore interactions in seagrass meadows Jour-nal of Experimental Marine Biology and Ecology 330420ndash436DOI 101016jjembe200512044

HemmingaMA Duarte CM 2000 Seagrass ecology Cambridge Cambridge UniversityPress

Hiebert TC 2015 Ampithoe lacertosa In Hiebert TC Butler BA Shanks AL edsOregon estuarine invertebrates Rudysrsquo illustrated guide to common species 3rd editionCharleston University of Oregon Libraries and Oregon Institute of Marine Biology

Hoegh-Guldberg O Bruno JF 2010 The impact of climate change on the worldrsquosmarine ecosystems Science 3281523ndash1528 DOI 101126science1189930

Hovel KA Fonseca MS Myer DL KenworthyWJWhitfield PE 2002 Effects ofseagrass landscape structure structural complexity and hydrodynamic regime onmacrofaunal densities in North Carolina seagrass bedsMarine Ecology Progress Series24311ndash24 DOI 103354meps243011

Hughes ARWilliams SL Duarte CM Heck KLWaycott M 2009 Associations ofconcern declining seagrasses and threatened dependent species Frontiers in Ecologyand Evolution 7242ndash246 DOI 101890080041

Iizumi H Taguchi S Minami T Mukai H Maekawa S 1996 Distribution and variabilityof nutrients chlorophyll a particulate organic matters and their carbon andnitrogen contents in Akkeshi-ko an estuary in northern Japan Bulletin of theHokkaido National Fisheries Research Institute 5943ndash67

ImajimaM (ed) 1996 Polychaetous Annelids Tokyo AquabiologyImajimaM (ed) 2001 Polychaetous Annelids II Tokyo AquabiologyJernakoff P Brearley A Nielsen J 1996 Factors affecting grazer-epiphyte interactions in

temperate seagrass meadows Oceanography and Marine Biology An Annual Review34109ndash162

Kanamori M Goshima S Mukai H 2004 Seasonal variation in host utilization ofepiphytic Lacuna species in mixed algal and surfgrass stands in JapanMarine Ecology2551ndash69 DOI 101111j1439-0485200400014x

KasimMMukai H 2006 Contribution of benthic and epiphytic diatoms to clam andoyster production in the Akkeshi-ko estuary Journal of Oceanography 62267ndash281DOI 101007s10872-006-0051-9

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 1922

Kuznetsova A Brockhoff PB Christensen RHB 2014 lmerTest tests for random andfixed effects for linear mixed effect models (lmer objects of lme4 package) R packageversion 20ndash11

Lee SY Fong CWWu RSS 2001 The effects of seagrass (Zostera japonica) canopystructure on associated fauna a study using artificial seagrass units and samplingof natural beds Journal of Experimental Marine Biology and Ecology 25923ndash50DOI 101016S0022-0981(01)00221-0

Lefcheck JS VanMontfrans J Orth RJ Schmitt EL Duffy JE LuckenbachMW2014 Epifaunal invertebrates as predators of juvenile bay scallops (Argopectenirradians) Journal of Experimental Marine Biology and Ecology 45418ndash25DOI 101016jjembe201401014

Long HA Grosholz ED 2015 Overgrowth of eelgrass by the invasive colonial tunicateDidemnum vexillum consequences for tunicate and eelgrass growth and epifaunaabundance Journal of Experimental Marine Biology and Ecology 473188ndash194DOI 101016jjembe201508014

Marchini A Sorbe J Torelli F Lodola A 2014 The non-indigenous Paranthura japonicaRichardson 1909 in the Mediterranean Sea travelling with shellfishMediterraneanMarine Science 15545ndash553 DOI 1012681mms779

Maxwell PS Ekloumlf JS Van Katwijk MM OrsquoBrien KR De la Torre-CastroM BostroumlmC Bouma TJ Krause-Jensen D Unsworth RKF Van Tussenbroek BI Van derHeide T 2016 The fundamental role of ecological feedback mechanisms in seagrassecosystemsmdasha review Biological Reviews DOI 101111brv12294

Meager JJ Schlacher TA GreenM 2011 Topographic complexity and landscapetemperature patterns create a dynamic habitat structure on a rocky intertidal shoreMarine Ecology Progress Series 4281ndash12 DOI 103354meps09124

Nakamachi T Ishida H Hirohashi N 2015 Sound production in the aquatic isopodCymodoce japonica (CrustaceaPeracarida) The Biological Bulletin 229167ndash172DOI 101086BBLv229n2p167

Nishimura S (ed) 1992Guide to seashore animals of Japan with color pictures and keysvol 1 Osaka Hoikusha (in Japanese)

Nishimura S (ed) 1995Guide to seashore animals of Japan with color pictures and keysvol 2 Osaka Hoikusha (in Japanese)

Nordlund LM Koch EW Barbier EB Creed JC 2016 Seagrass ecosystem services andtheir variability across Genera and geographical regions PLOS ONE 11e0163091DOI 101371journalpone0163091

Okutani T 2000Marine mollusks in Japan Tokyo University of Tokyo PressOumlstman Ouml Ekloumlf J Eriksson BK Olsson J Moksnes PO BergstroumlmU 2016 Topdown

control as important as nutrient enrichment for eutrophication effects in NorthAtlantic coastal ecosystems Journal of Applied Ecology 531138ndash1147DOI 1011111365-266412654

Poore AGB Campbell AH Coleman RA Edgar GJ Jormalainen V Reynolds PL SotkaEE Stachowicz JJ Taylor RB Vanderklift MA Duffy JE 2012 Global patterns

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 2022

in the impact of marine herbivores on benthic primary producers Ecology Letters15912ndash922 DOI 101111j1461-0248201201804x

RDevelopment Core Team 2015 R a language and environment for statisticalcomputing Vienna R Foundation for Statistical Computing

Robbins BD Bell SS 1994 Seagrass landscapes a terrestrial approach to the marinesubtidal environment Trends in Ecology and Evolution 9301ndash304DOI 1010160169-5347(94)90041-8

SawamuraM 1999 One-year comparison of stomach contents among demersal fishesoff the coast of Usujiri Hokkaido Japanese Journal of Benthology 5414ndash23 (inJapanese with English abstract) DOI 105179benthos5414

Somero GN 2002 Thermal physiology and vertical zonation of intertidal animalsoptima limits and costs of living Integrative and Comparative Biology 42780ndash789DOI 101093icb424780

Sudo H Azeta M 1992 Selective predation on mature male Byblis japonicas (Am-phipoda Gammaridea) by the barface cardinalfish Apogon semilineatusMarineBiology 114211ndash217 DOI 101007BF00349521

Suh HL Yu OH 1997Winter zonation of the benthic amphipods in the sandy shore surfzone of Dolsando southern Korea (in Korean with English abstract) Korean Journalof Fisheries and Aquatic Sciences 30340ndash348

ThomsenMS 2010 Experimental evidence for positive effects of invasive seaweedon native invertebrates via habitat-formation in a seagrass bed Aquatic Invasions5341ndash346 DOI 103391ai20105402

Toyohara T NakaokaM Tsuchida E 2001 Population dynamics and life history traitsof Siphonacmea oblongata Yokohama on seagrass leaf in Otsuchi Bay (SiphonariidaePulamonata) Venus (Jap J Malaco) 6027ndash36

Unsworth RKF Collier CJ Waycott M Mckenzie LJ Cullen-Unsworth LC 2015A framework for the resilience of seagrass ecosystemsMarine Pollution Bulletin10034ndash46 DOI 101016jmarpolbul201508016

Valentine JF Duffy JE 2006 The central role of grazing in seagrass ecology In LarkumAWD Orth RJ Duarte CM eds Seagrasses biology ecology and conservation TheNetherlands Springer 463ndash501

Valentine JF Heck Jr KL 1999 Seagrass herbivory evidence for the continued grazing ofmarine grassesMarine Ecology Progress Series 176291ndash302DOI 103354meps176291

Watanabe K Minami T Iizumi H Imamura S 1996 Interspecific relationship by com-position of stomach contents of fish at Akkeshi-ko an estuary at eastern HokkaidoJapan (in Japanese with English abstract) Bulletin of the Hokkaido National FisheriesResearch Institute 60239ndash276

WatanabeM NakaokaMMukai H 2005 Seasonal variation in vegetative growth andproduction of the endemic Japanese seagrass Zostera asiatica a comparison withsympatric Zostera marina Botanica Marina 48266ndash273 DOI 101515BOT2005036

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 2122

WhalenMA Duffy JE Grace JB 2013 Temporal shifts in top-down vs bottom-upcontrol of epiphytic algae in a seagrass ecosystem Ecology 94510ndash520DOI 10189012-01561

Yamada K Hori M Tanaka Y Hasegawa N NakaokaM 2007b Temporal and spatialmacrofaunal community changes along a salinity gradient in seagrass meadows ofAkkeshi-ko estuary and Akkeshi Bay northern Japan Hydrobiologia 592345ndash358DOI 101007s10750-007-0767-6

Yamada K Hori M Tanaka Y Hasegawa N NakaokaM 2010 Contribution ofdifferent functional groups to the diet of major predatory fishes at a seagrassmeadow in northeastern Japan Estuarine Coastal and Shelf Science 8671ndash82DOI 101016jecss200910015

Yamada K Takahashi K Vallet C Taguchi S Toda T 2007a Distribution life historyand production of three species of Neomysis in Akkeshi-ko estuary northern JapanMarine Biology 150905ndash917 DOI 101007s00227-006-0403-4

Ysebaert T Herman PMJ Meire P Craeymeersch J Verbeek H Heip CHR 2003Large-scale spatial patterns in estuaries estuarine macrobenthic communities inthe Schelde estuary NW Europe Estuarine Coastal and Shelf Science 57335ndash355DOI 101016S0272-7714(02)00359-1

YuOH Jeong SJ Suh HL 2008 Reproductive pattern of the epifaunal amphipodPontogeneia rostrata (Crustacea) on Dolsando Sandy Shore in Korea Ocean ScienceJournal 43127ndash133 DOI 101007BF03020693

YuOH Suh HL 2011 Secondary production of the eusirid amphipod Pontogeneiarostrata Gurjanova 1938 (Crustacea Peracarida) on a sandy shore in Korea OceanScience Journal 46211ndash217 DOI 101007s12601-011-0017-8

Zuur AF Ieno ENWalker N Saveliev AA Smith GM 2009Mixed effects models andextensions in ecology with R New York Springer

Momota and Nakaoka (2017) PeerJ DOI 107717peerj2952 2222