Seasonal and spatial variability in rates of primary production and detritus release by intertidal stands of Laminaria digitata and Saccharina latissima on wave-exposed shores in the northeast Atlantic

Abstract

Coastal habitats are increasingly recognized as fundamentally important components of global carbon cycles, but the rates of carbon flow associated with marine macrophytes are not well resolved for many species in many regions. We quantified density, rates of primary productivity, and detritus production of intertidal stands of two common intertidal kelp species-Laminaria digitata (oarweed) and Saccharina latissima (sugar kelp)-on four NE Atlantic rocky shores over 22 months. The density of L. digitata was greater at exposed compared to moderately exposed shores but remained consistently low for S. latissima throughout the survey period. Individual productivity and erosion rates of L. digitata did not differ between exposed and moderately exposed shores but differed across exposure levels throughout the year at moderately exposed sites only. Productivity and erosion of S. latissima remained low on moderately exposed shores and showed no clear seasonal pattern. Patterns of productivity and total detrital production (erosion and dislodgement) per m2 of both L. digitata and S. latissima followed closely that of densities per m2, peaking in May during both survey years. Temperature and light were key factors affecting the productivity rates of L. digitata and S. latissima. Erosion rates of L. digitata were affected by wave exposure, temperature, light, grazing, and epiphyte cover, but only temperature-affected erosion of S. latissima. Production of biomass and detritus was greater in L. digitata than in S. latissima and exceeded previous estimates for subtidal and warmer-water affinity kelp populations (e.g., Laminaria ochroleuca). These biogenic habitats are clearly important contributors to the coastal carbon cycle that have been overlooked previously and should be included in future ecosystem models. Further work is required to determine the areal extent of kelp stands in intertidal and shallow subtidal habitats, which is needed to scale up local production estimates to entire coastlines.

Full text

Ecology and Evolution. 2023;13:e10146.  
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https://doi.org/10.1002/ece3.10146
www.ecolevol.org
Received:11Januar y2023
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Revised:2M ay2023
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Accepted :9May2023
DOI: 10.1002/ece 3.10146
RESEARCH ARTICLE
Seasonal and spatial variability in rates of primary production
and detritus release by intertidal stands of Laminaria digitata
and Saccharina latissima on wave- exposed shores in the
northeast Atlantic
Abby R. Gilson1 | Lydia J. White1,2 | Michael T. Burrows3 | Dan A. Smale4 |
Nessa E. O'Connor1
This is an op en access arti cle under the ter ms of the CreativeCommonsAttributionL icense,whichpe rmitsuse,dis tribu tionandreprod uctioninanymed ium,
provide d the original wor k is properly cited.
©2023TheAuthors .Ecolog y and Evoluti onpublishedbyJo hnWiley&S onsLtd.
1SchoolofBiologicalSciences,Instituteof
GlobalFoodSecurity,Queen'sUniversit y
Belfas t,Bel fast ,UK
2TvärminneZoologic alStation,Universit y
ofHelsinki,Hanko,Finlan d
3ScottishAsso ciationforMarineScience,
ScottishMarin eInstitute,Oban,UK
4MarineBiologicalAssociationoftheUK,
Plymou th,UK
Correspondence
AbbyR.G ilson,TrinityCollegeDublin,
SchoolofNatura lSciences,Trinit yCollege
Dublin ,Dublin2,Irela nd.
Email: gilsona@tcd.ie
Present address
AbbyR.G ilsonandNessaE.O’Connor,
TrinityCol legeDub lin,SchoolofNatural
Science s,TrinityCollegeD ublin ,Dublin2,
Ireland
Funding information
Depar tmentforEconomyNorthern
Ireland; Department for Environment,
FoodandRu ralAf fairs ,UKGover nment ,
Grant /AwardNumber:NE/L 003279/1;
NaturalEnvironmentResearchCo uncil;
UKResearchandIn novatio nFuture
Leader sFellowship,Gr ant/Award
Number:MR/S032827/1
Abstract
Coastalhabitatsareincreasinglyrecognizedasfundamentallyimportantcomponents
ofglobalcarbon cycles,buttheratesofcarbon flowassociatedwithmarinemacro-
phytes are notwellresolved formanyspeciesinmanyregions. We quantified den-
sity, rates of primary productivity, and detritus production of intertidal stands of two
common intertidal kelp species— Laminaria digitata (oarweed) and Saccharina latissima
(sugarkelp)—onfourNEAtlanticrockyshoresover22 months.ThedensityofL. digi-
tatawasgreater at exposed comparedtomoderatelyexposedshores but remained
consistently low for S. latissima throughout the survey period. Individual productivity
and erosion rates of L. digitatadidnotdifferbetweenexposedandmoderatelyex-
posedshoresbutdifferedacrossexposurelevelsthroughouttheyearatmoderately
exposed sites only. Productivity and erosion of S. latissima remained low on moder-
ately exposed shores and showed no clear seasonal pattern. Patterns of productivity
and total detrital production (erosion and dislodgement) per m2ofbothL. digitata and
S. latissima followed closely that of densities per m2,peakinginMayduringbothsur-
vey years. Temperature and light were key factors affecting the productivity rates of
L. digitata and S. latissima. Erosion rates of L. digitatawereaffectedbywaveexposure,
temperature, light, grazing, andepiphytecover,butonly temperature-affectedero-
sion of S. latissima.ProductionofbiomassanddetrituswasgreaterinL. digitata than
in S. latissimaandexceededpreviousestimatesforsubtidalandwarmer-wateraffin-
ity kelp populations (e.g., Laminaria ochroleuca). These biogenic ha bitats are cle arly
importantcontributorstothecoastalcarboncyclethathavebeenoverlookedprevi-
ouslyandshouldbeincludedinfutureecosystemmodels.Furtherworkisrequiredto
determine the arealextentofkelp standsinintertidalandshallowsubtidal habitats,
which is needed to scale up local production estimates to entire coastlines.

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1 | INTRODUCTION
Coastal vegetative habitats (e.g., mangrove forests , salt marshes,
seagrass meadows) have long been recognized as important car-
bon sink s (i.e., blue c arbon) owing to e xtreme ly high rates of p ro-
ductivity andcapacit y for localcarbonstorage(Bauer et al.,2013;
Duarte, 2017; Duarte et al., 2005).Increasingly,macroalgalhabitats
(i.e.fucoidandkelpforests)areincludedintheblue carbonconver-
sation due to their ex tremely high productivity and spatial extent
(Pessarrodona et al., 2022) even tho ugh they do not s tore carb on
locallywithin sediment s. Carbon flows through these coastal eco-
systems via multiple trophic pathways, many of which play a fun-
damentalroleinregulatingrates of ecosystem functioning(Byrnes
et al., 2011;Stenecketal.,2002). These pathways, however, remain
unresolvedinmany systemsand the mechanisms by whichcarbon
flows through dif ferent compartmentsof the coastal carbon cycle
are understood poorly.
Macroalgalhabitatsrepresentthemostproductiveandextensive
ofthecoastalvegetativehabitats(Duar te,2017; Duarte et al., 2022),
with max imum product ivity esti mates exceeding ~1000 gC m−2 year−1
inthe Nor th Atlantic (Mann,1973 , 2009) and ~50 00 g C m−2 year−1
globally (Pessarrodona et al.,2022). It is estimated that intertidal
andsubtidalmacrophytesmaycontributeupto45%oftotalprimary
productioninsomenear-coastalsystems(Smaleetal.,2013).Most
ofthisproductioncomesfromlargebrownseaweeds(e.g.,kelpsand
fucoids), which form extensive stands, primarily along temperate
and polar rocky coastlines (Duar te et al., 2022;Stenecketal.,2002).
Thesehabitatsarecharacterizedbyex tremelyhighratesof carbon
fixation, supporting highsecondary production and creating biodi-
versity hotspots that support many commercially import ant species
(Smale et al., 2013). Kelp productivit y correlates strongly with a
number of environmental variables, including nutrients, light,tem-
peratu re, and wave exposure (d e Bettignies et al ., 2013; Graham
et al., 20 07; Hurd, 2000; Krumhansl & Scheibling, 2012; Smale
et al., 2016, 2020). This sensitivity to environmental factors has re-
sulted in significantchanges to productivityand biomass,with the
potentialtohavelargeindirecteffectsoncoastalfoodwebsandul-
timately ecosystemfunctioning and stabilityunder futureenviron-
mentalchangescenarios(Wernbergetal.,20 19).
The majority of kelp- derived production (>80%) enters the
foodweb throughdetritalpathways,withhighratesofexportfrom
source populations and the potential for long- distance transport to
recipientecosystems(Krumhansl& Scheibling,2012). This transfer
ofcarbonhasbeenshownto constituteacrucialtrophicsubsidyin
arangeof habitats,includingrocky shores,sandy beaches, subma-
rinecanyons,andthedeep-sea(Gilson,Smale,Burrows,etal.,2021;
Krumhansl & Scheibling, 2012; Polis et al., 1997). Detrital produc-
tion is gene rated by two prim ary mechan isms, chronic er osion of
material (typicallyfromthedistalpartoftheblade)ordislodgment
ofsectionsorentire thalli (de Bettignies et al.,2013; Krumhansl&
Scheibling, 2011). Depending on the mechanism detrital proper-
ties, suchasparticlesizeand density,c an varyand influencerates
of transport and consumption (Filbee-Dexter et al., 2018). Wave
action is oftenconsideredtobetheprimarydriver ofkelpdetritus
production, owing to the accumulation of wrack in coastal habi-
tats af ter storms andthe higher ratesof removal obser ved during
storms,particularlyforwholethalli(Dayton&Tegner,1984;Milligan
&DeWreede, 2000;Seymouretal., 1989). Temperature, however,
has been positively correlated witherosion rates, with higherero-
sion rates t ypically occurring during summer and autumn months
(de Bettignies et al., 2013; Hereward et al., 2018; Krumhansl &
Scheibling, 2011). Biol ogical fac tors, such a s epiphyte cove r,gra z-
ing press ure, and kelp fec undity, have also b een linked to eros ion
ratesthroughthestructuralweakeningofkelptissue(deBettignies
et al., 2013).
Althoughdataremainrelativelylimited,arecentsurgeinresearch
efforts has yielded import ant insights into primary production and
detritusreleaseinkelpforests(Dolliver&O'Connor,2022). Despite
this, studies are largely restric ted to a few geographical areas, par-
ticularlyAustralasiaandNorthAmerica,withcomparativelyfewerin
Europe, including IrelandandtheUK(Smale etal., 2013). In recent
years,workintheUKhasbeguntocharacterizekelpforeststructure
using sys tematic large -scale fi eld surveys , quantify ing the densit y
and dist ribution of subt idal kelp fores ts and linkin g regional-s cale
variability with environmental variables (Hereward et al., 2018;
Pessarrodona,Foggo,etal.,2018;Pessarrodona,Moore,etal.,2018;
Smaleetal.,2016, 2020;Smale&Moore,2017;Smithetal.,2022).
Few studies have quantified primary production or detrital re-
lease by intertidal kelp stands, despite clear differences in envi-
ronmental conditions, community composition, functional traits,
and food web struc ture between intertidal and subtidal habitats
(Hereward et al., 2018).Forexample,outof>1000globalestimates
ofmacroalgalprimaryproductivity,only37%areintertidalestimates
and <2% are intertidal kelps (Pessarrodona et al., 2021). Unlike
subtidal habitat s, theintertidal zoneis influenced by both oceanic
and atmospheric climates and experiences a steep stress gradient
associate d with tidal cyc les. It is expe cted, there fore, to exhibit a
pronounced response to climate change impacts that may dif fer sig-
nificantlyfromthoseseeninsubtidalhabitats(Hawkinsetal.,2009;
Helmuth et al., 2006).Althoughintertidalkelpstandsarerestricted
to the very low shore fringe and cover a much smaller area than
subtidal stands( Yessonetal.,2015), dominant species can occur in
KEYWORDS
carboncycle,detritalproduction,ecosystemfunctioning,Laminaria digitata, macroalgae,
primary productivity, Saccharina latissima, temperate reefs
TAXONOMY CLASSIFICATION
Ecosystem ecolog y

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GILSON et al.
greater densities, suggesting that per area unit they may make sig-
nifica nt contributi ons to coastal p rimary pr oductivi ty. Reliable es-
timates ofcarbonfixationandfluxes are lackingforwave-exposed
extre me-low shore h abitats in mos t regions, howeve r, m ost likely
becauseoftheirinaccessibility.
Having identified these knowledge gaps, we estimated rates of
primar yproductionanddetritusreleasebyintertidalstands oft wo
kelp speci es widely dist ributed acros s the North At lantic. We ex-
amined seasonality and theinfluenceofwave exposure on carbon
dynamicsandtestedwhetherbiotic(grazingpressure,epiphytealgal
cover)and abiotic(temperature, light)factorsaf fectedkelpproduc-
tionandbreakdownonwave-exposedrockyshoresinthenortheast
Atlantic.
2 | METHODS
2.1 | Study design and location
Wequantified density, productivity,erosion, and dislodgement of
intertidal stands of Laminaria digitata and Saccharina latissima sea-
sonallyover2 years(inMay,August,andNovember2016;February,
May,August, and November 2017;Februar y 2018). For L . digitata,
we tested fo r the effect s of wave exposure by qu antifying t hese
aspects of kelp populations at two exposed (Ballywhoriskey and
Rinmore P oint) and two m oderately ex posed (Ball ywhoriskey P ier
andMelmoreHead)sites(Figure 1).Wequantifiedcarbondynamics
for S. latissima only at the t wo moderately exposed sites where it oc-
curred (Figure 1).Wealsoquantifiedgrazerabundanceanddamage,
epiphytic algal cover, temperature, and light levels as potentially im-
portantininfluencingtheobservedpatterns.Totestforanticipated
seasonal responses, sampling dates were chosen to reflect spring,
summer,autumn,andwinter.Somesamplingdates,however,donot
fall dist inctly wit hin meteorolog ical seasons ow ing to the 4 week-
period bet ween tagging individuals and datacollection.We,there-
fore, refer to them as sampling periods instead of seasons.
Sites were located on the NW coast of Ireland in Co. Donegal
andaretypicalofopencoastshoresinthewiderNEAtlanticregion
(Mrowicki et al., 2014; O'Connor et al., 2011). Sites were selected
based on their simulated average wave fetch (F) from a vector-
based digital coastline model (Ballywhoriskey 5415.9 m, Rinmore
Point 546 0.1 m, Ballyw horiskey Pier 12 24.8 m and Melmore H ead
1224.9 m;Figure 1; Burrows,2012).Allsiteswerecharacterized by
large gentl y sloping granite p latforms that wer e characterized b y
apatchwork ofbarnaclesandjuvenile mussel beds (particularly at
exposed sites), and dense macroalgal canopies interspersed with
patches of barerock. Onmoderately exposed shores, a bandof S.
latissima extend s below the fuc oid region, be fore giving way to L .
digitata bedsattheextremely low inter tidal zone(1.0–1.5 mabove
Chart Datum;Figure A1). On exposed shores, L. digitata dominates
the low shore and sparse stands of Alaria esculenta occur attached
to large bou lders loca ted within the kel p beds (0.86 ± 0.2 individ-
uals per m2). O n all shores, indi viduals of large brow n macroalga
Sacchoriza polyschides are interspersed sporadically among the dom-
inant kelp species(0.16 ± 0.03 individuals perm2 basedonquadrat
surveysdescribedbelow).
Toquantif ythedensityof bothkelp speciesateachsiteduring
each sampling per iod, stratified haphaz ard sampling was used to
FIGURE 1 Studysiteswereatexposed
(BallywhoriskeyPointandRinmorePoint)
andmoderatelyexposed(Ballywhoriskey
PierandMelmoreHead)shoresinCo.
Donegal, Ireland.

4 of 16
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GILSON et al.
place between 8and 10 quadrats(0.25 m2)on bedrock within the
kelpbedhabit at(0.3–0.8 mabovechar tdatum).The densityof ma-
ture L. digitata and S. latissima individuals (i.e. canopy formers) was
recordedineachquadrat.
To estimate the productivity rates of L. digitata and S. latissima
duringeachsamplingperiod,15–20maturecanopy-formingindivid-
uals (>1 m)ofeachspecieswereselectedrandomlyateachsiteand
tagged individually. Juvenile kelps were excluded from the current
study owing to their representation of only a small proportion of
these kelp populations and time constraints. In addition, juvenile
recruits are spatially patchy and constrainedbydifferent environ-
mentalvariables.Elongationratesandbiomassaccumulationofeach
individual were estimated using a modified hole- punch method (Tala
&Edding,2005).Some individuals were lostdueto wave dislodge-
mentsuchthatfinalsample sizes variedfrom3to17individualsof
eachspeciespersitepersamplingperiod.ForS. latissima, each indi-
vidualwaspunchedwithoneholeloc ated10 cmfromthestipe/lam-
inajunction.ForL. digitata,becauseitformsadigitatedblade,three
holes werepunched,the first and second 10 and 20 cm above the
base of the central lamina,respectively,andthethird 10 cm above
thebase of the bladeonthe firstdigit. Af ter 4 weeks,taggedindi-
viduals were relocated and growth was measured.For S. latissima,
the distance bet ween thefirsthole and the base of theblade and
thefinalbladelengthwerem easured.Thegrowthratewasthencal-
culated as:
where Hf is the final growth hole position (cm) and tisthenumberof
daysbetweeninitialandfinalmeasurement s(Tala&Edding,2005).For
L. digita ta,thedist anceof al lt hr eeholesfromth eb as eofthebl ad ew as 
measured and growth rate was then calculated using the mean of the
three measurements.
Productivity was calculated for each species as the average
estimateddry biomass per unit length for thebasal 1/3rd of the
thallus m ultiplied by t he growth ra te (g DW day−1). Dr y biomass
perunitleng thwasestimatedbytaking5 cmsectionsofthestipe,
basal,anddistal1/3rdoftheblade,andobtainingthewetweight
beforedryinginanovenat60 °Cu nti lconstantweight.Arelation-
shipbetweenwetand drybiomass (g cm−1 )was then established
forthe stipe,basal, anddistal 1/3rd of the bladeusing linearre-
gression ( p ≤ .05;R2 > .80).
Rates of detrital production in S. latissima, were estimated from
tissue loss fromthe thallus ( TL, cm) based on thechange in blade
lengthandbladegrowth:
where BLiand BLf are initial and final blade length (cm) and g is the
lengthofthenewtissueproduced(cm).ForL. digitata,thesameequa-
tionwasusedforboththecenterandouterdigitandanaveragetaken.
The rate of erosion (gDW day−1) was then calculated as the average
estimateddrybiomassperunitlengthforthedistal1/3rdoftheblade
multipl ied by the tissu e loss and divi ded by the numb er of days be-
tween sampling occasions.
To estimate kelp dislodgement rates, the 15–20 individuals
tagged previously were collected and dislodgement was assumed
frommissingtaggedindividuals.Dislodgementrate(%dislodgement
perday) wasthendefined asthedifferencebetweentheinitialand
final number of tag ged individuals between sampling periods di-
videdbytheinitialnumber.Dr ybiomasslossthroughdislodgement
wasthenestimatedusingtherelationshipbetweenwetanddrybio-
mass for the whole individual. Owing to adverse weather conditions,
datawerenotavailableforAugustandNovember2017.
To estimate daily productivity and erosion rates per unit area,
individual productivity and erosion rates for L. digitata and S. la-
tissimawere multiplied by the density of each species at eachsite
during each sampling period (per m2) obtained from density quad-
ratsurveys(gDW m−2 ). The rate of detrital production through dis-
lodgementperdaywascalculatedusinga similarconstruct butwas
furthermultipliedbythemeandrybiomassofadultkelpindividuals
and divided by the number of days betweensampling (g DW m−2 ).
For an annual estimate of production (productivity) and detrital
production (erosion and dislodgement) for L. digitata and S. latis-
sima, seasonally var ying rates were averaged over the whole year,
andestimatesofdailyrateswerethenmultipliedby365(gDW m−2 ;
Krumhansl&Scheibling,2 011).
Factors that may influence growth and detritus production
rates, in cluding grazer de nsity and damage , epiphytic alga l cover,
temperature, and lightwerealso quantified. Temperature and light
weremeasuredinsituusingHOBOtemperature/lightPendantdata
loggers mounted at each site at the relevant shore height. Detailed
methodstoquantifythesevariablesandgraphsshowingannualvari-
ationcanbefoundintheAppendix (Figures 3 and 4).
2.2 | Data analysis
To test for the effects of wave exposure (fixed, two levels), sampling
period (fixed, eight levels), and site (random and nested in wave ex-
posure, two levels) on L. digitata density, productivity and erosion
(individual and per m−2), and total detrital production, linear mixed
effectmodels fitted by maximum likelihood wereperformed using
the package lme4 (Zuur et al., 2009). Sampling period was treated
initially as a fixed factor so that we could test explicitly for putative
differences and identify which sampling times differed from each
other.Allmodelsincludedan interaction termbutwhennot signifi-
cant, interactions were removed and the model was re- fitted with
maintermsonly.Ifmodelassumptionsweremet,type2ANOVAwas
usedtoobtainχ2 and p- values (package car;Fox&Weisberg,2011).
Where p-values were significant, Tukey HSD adjusted pairwise
comparisonsusingleast-squaremeanswereusedforposthoccom-
parisons (package lsmeans; Lenth, 2018). Residuals were visually in-
spectedandQQplotswereusedtocheckassumptionsofnormality
andhomogeneity ofvariance.Whereresidualsdidnot meetmodel
assumptions despite the transformation,data were analyzed using
G=(Hf −10)∕t,
TL =(BLi +g)−BLf,

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GILSON et al.
a general ized linear mixe d model with a Tweedie d istribut ion that
alsoaccountsforzeroinflation(packageTweedie;Arcutietal.,2013).
Wheresamplingperiodscontainedonlyonelevelofwaveexposure
or site owing to logistic al difficulties preventing data collection at
certain sites, those time points were excluded from the analysis.
AnalysisofS. latissimafollowedasimilarconstructbutwithoutwave
exposurebecausethiskelpspecieswasonlyfoundonthetwomod-
erately exposed shores. Owing to only two replicates per treatment,
dislodgement rate, and detrital production through dislodgement
werenotanalyzedstatisticallyandonl ypat ternsinthedataarepre-
sentedforobservation.
To test whether biotic (fixed: distal area grazed, total grazer
abundance,epiphyticalgalcover)andabiotic(fixed: meanandmax-
imum temperature, mean and maximum light, daily cumulative irra-
diance, wave exposure) factors affected production and erosion of
L. digitata and S. latissima,linearmixedeffectmodelswereused.Site
and sampling period were treated as random fac tors in the model as
wewerenotinterestedintestingfordifferencesbetweensampling
periodsspecifically,butforrelationships between explanatory and
predictorvariables. All remaining main termswereincludedinthe
model an d model selec tion was per formed using Ak aike informa-
tioncriterion(AIC)valuesandweights,wherethelowestAICvalues
representedtheoptimalmodel (Ahoetal.,2014; Zuur et al., 2009).
ResidualswerevisuallyinspectedandQQplotswereusedtocheck
ass um ptionsofnormalit yandho mo geneit yof va riance.Wh er esam-
pling periods contained only one level of wave exposure or one site
owing to logistical difficulties preventing data collection at certain
sites,thosetimepoint swereexcludedfromtheanalysis.Allanalyses
were conducted using R version 3.3.4 (R Development Core Team,
2017 ).
3 | RESULTS
The density of L. digitata differed among wave exposures
(
𝜒2
1,2
= 20.484; p < .001)andsampling periods(
𝜒2
1,6
= 14.175;p < .01).
Post hoc tests showed that L. digitata density on exposed shores
(28.74 ± 1.43 indiv iduals per m2) was twice that of moderately ex-
posedshores(15.05 ± 1.35individualsperm2) and density was gen-
erally g reatest in Febr uary or May at b oth exposur es during both
survey years (Figure 2a). No sign ificant effe ct of sampling p eriod
on the density of S. latissima was identified, with density remaining
consistently low throughout the survey period (
𝜒2
1,6
= 10.28; p = .1;
7.32 ± 1.38individualsperm2; Figure 2b).
Asignificant interaction between wave exposure andsampling
period on the productivity of L. digitata was identified (Table 1;
Figure 2c). Specifically, wave exposures did not dif fer from each
other within sampling periods owing to the variable nature of
these data. There were significant differences between sampling
periods, however, that were not consistent across wave expo-
sures. Sp ecifically, sampling periods at exposed sites did not dif-
ferfrom each otherbut atmoderately exposed sites, May of 2016
(0.35 ± 0.0 3 g DW day−1) was significantly greater than most other
samplin g periods and Novem ber of 2017 (0.18 ± 0.01 g DW day−1)
significantly lower (see Table S1a for all post-hoccomparisons). A
significantinteractionbetweenwaveexposureandsamplingperiod
was also identified for productivity per m2 of L. digitata (Table 1;
Figure 2e).Asseenforindividualproductivity,waveexposurelevels
didnotdifferwithinsamplingperiodsbutdifferedbetweensampling
periods inconsistently across wave exposure levels. Specifically,
at exposed sites, February of 2017 (13.48 ± 1.5 g DW day−1 ) was
greater th an most other s ampling pe riods and Novem ber of 2017
wassignificantly lower(2.5 ± 0.28 gDW day−1; Table S1b). The pro-
ductivity of S. latissima also differed bet ween sampling periods
(
𝜒2
1,7
= 25.57;p < .001;Figure 2d). Post hoc tests identified the great-
est rate s in May (0.3 ± 0.05 g DW day−1) a nd lowest in Novembe r
(0.12 ± 0.01 g DW day−1 ), but conversely, peaked in November in
2017(0.34 ± 0.08 gDW day−1). Productivity per m2 of S. latissima did
notfollowpatternsofindividualproductivityratebutratherthatof
density,withthegreatestproductivityduringMayofboth2016and
2017(
𝜒2
1,6
= 164.37;p < .001;Figure 2f).
Erosion rat es did not differ b etween levels of wave ex posure
within sampling periods but differed between sampling periods
inconsistently across wave exposure levels (Table 1; Figure 3a).
Samplin g periods at expo sed sites did not dif fer from each ot her
but at moderately exposed sites, May 2016 (1.7 ± 0.32 g DW day−1 )
was significantly greater than all other sampling periods (Table S1c).
Erosion rates of S. latissima differed between sampling periods
(
𝜒2
1,7
= 20.43; p = .004), with the greatest ratesin May in both 2016
and2017(0.45 ± 0.11and0.57 ± 0.19 gDW day−1 , respec tively) and
lowest dur ing November in 2016 bu t August in 2017 (0.16 ± 0.01
and0.27 ± 0.06 gDW day−1 , respectively; Figure 3b).
Althoughdislodgementdatacould notbestatisticallyanalyzed,
it appears that at exposed sites, dislodgement rates of L. digitata
weregreatestinAugustandFebruaryof2016and2017(Figure 3c).
RatesofdislodgementforbothL. digitata and S. latissima at moder-
atelyexposedsites, however,weregreatestinNovember2016and
Februar y2017(Figure 3c,d,respectively).Meandetritalproduction
through dislodgement by L . digitata was greater at exposed sites
during AugustandFebruar yof2016 and 2017,respectively,but at
moderately exposed sites, L. digitata and S. latissimabothpeakedin
NovemberandMay(Figure 3e,f, respectively).
Total detrital production of L. digitatadidnotdifferbetweenex-
posurelevelswithinsamplingperiodsowingtohighvariabilityinthe
datasetbutdif feredinconsistentlybetweensamplingperiodsacross
levels of wave exposure (Table 1; Figure 3g).Atexposedsites,May
2016(16.52 ± 3.18 gDW day−1)wasgreaterthanFebruary2018only
(3.28 ± 0.52 gDW day−1).Atmoderatelyexposedsites,however,May
2016 (28.4 ± 5.67 g DW day−1) was greater than all other sampling
periods (Table S1d). Total detrital production of S. latissima followed
a similar pat tern to density (per m2)anddif fered betweensampling
periods (
𝜒2
1,5
= 15.79;p = .007),withthegreatestdetritalproduction
inMayofboth2016and2017(Figure 3h).
Monthlymean(negativelyrelated)andmaximum(positivelyre-
lated) temperature were identified as key factors affec ting individ-
ual productivity rates of L. digitata (R2 = 33.8% ; Table 2). Similarly,

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GILSON et al.
individual productivity rates of S. latissima were correlated with
monthly mean (negatively related) and maximum (positively related)
temperature and maximum light (negatively related; R2 = 26.4%;
Table 2).Wave exp osure (positive ly related), mon thly mean (posi-
tively related), maximum (negatively related) temperature, maximum
light (negatively related), daily cumulative irradiance (negatively
FIGURE 2 Mean(±SE)density(m−2 ),individualproductivity(gDW day−1) and productivity per m−2(gDW m−2 day−1 ) of Laminaria digitata
(a, c, and e, respectively) and Saccharina latissima(b,d,andf,respectively)basedonfoursitesattwodifferentlevelsofwaveexposurein
Co. Donegal, Ireland. n = 8–32.Aug,August;Feb,February;Nov,November.Blackcirclesrepresentsamplingperiodsinwhichdataare
unavailable.

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related), grazing (positively related), and epiphytecover (positively
related) were identified as factors affecting the individual erosion
rate of L. digitata (R2 = 31.8%; Table 2). Individual erosion rates of
S. latissima, however, were correlated with monthly mean (pos-
itively related) and maximum temperature (negatively related;
R2 = 16.4%;Table 2;Figuresillustratingallquantifiedvariablesarein
FiguresA2 and A3).
4 | DISCUSSION
We identified a seasonal pattern in individual productivity rates
for L. digitata and S. latissima that is aligned with many other kelp
species globally,with apeakin production inlatewinterandspring
(Februar y/May) and seasonal low in autumn (November; Brady-
Champb ell et al., 1984; Fairhead & Cheshire, 2004; Kr umhansl &
Scheibling, 2011; Mann, 1973; Miller et al., 2011; Pessarrodona,
Moore, et a l., 2018; Tala & Edding, 2005). This cyc le is driven by
changes in photoperiod and annual temperature fluctuations, which
arein turn linked tonutrientdynamics andwaveexposure (Bekkby
et al., 2014;Hepburnetal.,2007;Kain,1979 ; Pedersen et al., 2012;
Reed et al., 2011).T hisi ss up por tedbyt heident if icati on oftemp er a-
ture and light as key factors affecting individual productivity rates
ofthesekelpspecies, accountingforbetween26%and34%of the
observedvariationinthedata.PeakgrowthratesofL. digitata(0. 39–
0.49 gDW day−1 ) and S. latissima(0.34DW g day−1) were lower than
estimat es for their su btidal counte rpart L. hyperborea (0.78–0.87 g
DW day−1) and the warm- water kelp Laminaria ochroleuca (0.63 g
DW day−1; Pess arrodona , Foggo, et al., 2018). On an ann ual basis,
however, owing to their continual growth throughout the year, mean
annual productivity rates are comparable acrossspecies through-
out the region (L. digitata 0.29–0.38 g DW day−1; L. hyperborea
0.19 gDW day−1; L. ochroleuca0.33–0.37 gDW day−1; Pessarrodona,
Foggo, et al. , 2018). Predicted increases in temperature under cli-
mate change scenarios (IPCC, 2022) are, therefore, likely to signifi-
cantly reduce the productivity of these kelp species, slowing rates
of carbo n fixation an d storage (Ha rley et al., 2006; Pessarrodona,
Moore,etal.,2018).
Both studied species released detritusvia erosion of the distal
partsof the bladethroughouttheyear,providingaconsistent flow
of organic matter from kelp stands. This is in contrast to another co-
occurring species L. hyperboreawhichischaracterizedbyadiscrete
phase of detrital production in which the old lamina is shed during
the months of March–May (Kain & Jones, 1971; Pessarrodona,
Foggo,etal.,2018;Pessarrodona,Moore,etal.,2018). Peak erosion
rates of L. digitataatboth waveexposuresrangedbetween0.6and
1.7 g DW day−1 and were ~0.6 g DW day−1 for S. latissima, which is
higher than previous rates recorded for populations of L. hyperborea
and L. ochroleuca along the UK coastline (Pessarrodona, Moore,
et al., 2018).SeasonallowsforbothL. digitata(0.2–0.26 gDW day−1)
and S. latissima (0. 26 g DW day−1) were still greater than the mean
annual erosion rate of L. hyperborea (~0.19 gDW day−1 ) and only mar-
ginally lower than L. ochroleuca (~0.3 3 g DW day−1; Pessarrodona,
Foggo,etal.,2018).Whenconsideringhabitatextent,however,itis
likely that L. hyperboreapopulationsmake greater contributionsto
the detritus pool, given the greater areal coverage and depth pene-
tration than L. digitata(Smithetal.,2022).Evenso,thecontribution
of intert idal kelp stan ds to coastal det rital pools , which has been
largelyoverlooked,islikelytobesignificant.
Waveexposure wasidentifiedasasignificant fac tor positively
affecting erosion rates of L . digitata, which is in line with previous
studiesinotherregions(deBet tigniesetal.,2012, 2013;Krumhansl
&Scheibling,2011).Inintertidalhabitats,individualsaresubjected
to heavy w ave action that ca n cause physica l damage (i.e., abr a-
sion, breakage) and contribute to detrital production (Dobrynin
et al., 2010; Mac h et al., 2007). Erosion rates of L. digitata and S.
latissimawerealsocorrelatedwithtemperature,light,grazing,and
epiphytic algal cover, all of which fluctuated markedly throughout
the survey period and exhibit high seasonalit y (Figures A2 and
A3). Increas ed temperat ure has been li nked to tissue de gradatio n
in kelps,re ducingtensile stre ngth and increasing susceptibility to
erosionduringwarmperiods(Krumhansl&Scheibling,2011, 2012;
TAB LE 1 Linearmixedeffectsmodeltestingforeffec tsofwaveexposureandsamplingperiodontheproductivity(g day−1), productivity
per m−2(gDW day−2),anderosionrate(g day−1) of Laminaria digitata.Sampleswerecollectedatfoursites,twoexposedandtwomoderately
exposed, during eight consecutive sampling periods. Individual sites nested in wave exposure were included as a random factor in the
statisticalmodel.Significantresultsareinbold(p < .05).
Productivit y (g day−1)Productivity (g DW m−2 day−1 )
df χ2p- Value df χ2p- Value
Waveexposure(W) 12 .78 .09 12.01 .15
Samplingperiod(SP) 672.48 <.001 676 .84 <.0 01
W × SP 615 .76 .01 516 .64 .005
Erosion (g day−1)Total detrital production (g DW m−2 day−1)
df χ2p- Value df χ2p- Value
Waveexposure(W) 15.79 .01 10.05 .8
Samplingperiod(SP) 697. 28 <.001 673.85 <.001
W × SP 635.72 <.001 520.27 .001

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FIGURE 3 Mean(±SE)rateoferosion(gDW day−1),dislodgement(%m−2 day−1 ),detritalproductionthroughdislodgement(DW m−2 day−1 ),
andtotaldetritalproduction(viaerosionanddislodgement;gDW m−2 day−1) of Laminaria digitata (a, c , e, and g, respectively) and Saccharina
latissima(b,d,f,andh,respectively).DatawerebasedonfoursitesattwodifferentlevelsofwaveexposureinCo.Donegal,Ireland.n = 2.
DataforAugustandNovember,2017areunavailable.

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Rothäusler et al., 2009). Higher temperatures experienced during
summer are, however, also associated with increased grazer
abundances and consumption rates that can further exacerbate
tissue damage (Gilson, Smale, & O'Connor, 2021; Krumhansl &
Scheibling,2011;Toth&Pavia,2002). Increased cover of epiphy tes
also generally occurs through summer when temperatures are high,
isoftenindicativeofsenescingkelptissue,andcanincreasebreak-
ageanddetritusproduction(Scheibling&Gagnon,2009).Whileitis
notpossibletodisentangletherelativeimportanceofthesefactors
inthecurrentstudy,particularlywhenvariabilityishigh,itis likely
they influenced detrital production rates and may to some extent
explain the obser ved variability between survey years. It is also
likely that other fac tors not considered in this study are important
drivers of detritus production, in particular for S. latissima in which
onlya smallproportion oftheobservedvariationwas explainedby
thepredictorvariablesincludedinthemodel.Forexample,thepro-
duction of reproductive sorus tissue in kelps, which also varies sea-
sonally,haspreviouslybeenlinkedtodetritalproductionratesand
may have accounted for increased erosion throughout autumn and
winter(deBet tigniesetal.,2013).
Althoughdatafordislodgementwasnotstatisticallyanalyzedand
variabilitywashigh,thereissometentativeevidenceofdifferences
TAB LE 2 Thebestmodelsofabiotic(waveexposure[WE],maximum[Tmax]andmeanmonthlytemperature[Tavg]),maximummonthlylight
(Lmax),dailycumulativeirradiance(DCI),andbiotic(epiphyticalgalcover[E%],distalareagrazed[G%],andtotalgrazerabundance[Abun])
factorsidentifiedtoexplainvariationinproductivity(g day−1)anderosion(g day−1) for Laminaria digitata and Saccharina latissima.
Variable Intercept Model parameters + slope Weight R2
L. digitata
Productivity −1.7 57 Tmax (0.015), Tavg(−0.029) 0.162 .338
Erosion −4.956 WE(+), Tmax(−0.022),Tavg(27.14),Lmax(−0.00 02),DCI
(−0.00002),E%(16.65),G%(46.90)
0.902 .318
S. latissima
Productivity −1.144 Tmax(0.089),Tavg(−0 .126)
Lmax(−0.0007)
0.162 .26 4
Erosion −6.996 Tmax(−0.6946),Tavg(3.192) 0.121 .194
FIGURE 4 Schematicshowingthemean(±SE)amountofcarbon(gDW m−2 day−1 ) fixed through primary production and lost through
detritalproduction(dislodgement,erosion,anddissolvedorganiccarbon(DOC)annuallyforLaminaria digitata and Saccharina latissima at two
moderatelyexposed(ME)andtwoexposed(E) Irish shores. n = 1 5 – 1 6 8 .
ME: 1.72 ± 0.84
?
ME: 11.02 ± 1.51
E: 11.31 ± 0.87
ME: 5.32 ± 1.54
E: 14.46 ± 4.03
ME: 3.55 ± 0.6?
ME: 5.99 ± 0.36
E: 8.69 ± 0.41
ME: 1.8 ± 0.2
Dislodgement ErosionDOC
Producon

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basedonshoreandsamplingperiod.Dislodgement ratesanddetri-
tal production through dislodgement of L. digitata were greater at
exposedsites, and during August–February at bothlevels of wave
exposure, which coincides with increased dislodgement during peri-
odsofheavywaveaction.August toNovemberis hurricaneseason
inthe NWAtlantic, bringingstrongwesterlywindsand largeswells
acrosstheAtlantic,whileDecember–Februaryisthewinterperiodin
NEAtlantic(e.g.,Brownetal.,2010;Wolf&Woolf,2006).Although
individuals of L. digitata were larger on average than S. latissima and
contribu ted greater qua ntities of detr itus to the detr ital pool, t he
ruffled margins of S. latissimacr eat ec o ns ide r abl ymo red rag tha nth e
flat lamina of L. digitata, accounting for their greater rates of dislodg-
mentevenatmoreshelteredsites(Buck&Buchholz,2005). S. latis-
simaalsoroutinelysettlesonsemi-stablerocksandcobblesinstead
ofemergentbedrock,particularlyinshelteredconditions,increasing
theirsusceptibility to dislodgement (Scheibling et al., 2009; Smale
&Vance,2016). In addition, individuals of L. digitata are morpholog-
ically adapted to wave- exposed conditions, with a larger, stronger
holdfastandstipeand morestreamlined bladesthatenablegreater
attachmenttothesubstrataandreducedrag.Althoughdislodgement
ratesforbothkelpspecieswerelowerthanthosereportedforsub-
tidal L. hyperborea populations (4%–27% m−2 year−1; Pessarrodona,
Moore, et al.,2018; Smaleetal.,2022),most likelybecauseof the
degreeofprotec tionsubtidalkelpforestsofferintertidalkelpbeds,
the greater population densities of L. digitata in intertidal habitats
recordedhereresultedinamuchlarger contributiontothedetrital
pool per unitarea. Clearly, predicted increasesinstorm frequenc y
arelikelytoleadtogreaterr atesofdislodgement(Feseretal.,2015;
IPCC, 2022), potentially increasing detrital resources within coastal
foodwebs.
Overall, erosion (rather than dislodgement) was the dominant
mechanismofdetritalproductionforbothL. digitata, at exposed and
moderately exposed sites, and S. latissima,accountingfor72%,77%,
and77%oftot aldetritalproduction,r espect ively(Figure 4). Total de-
trital production was greatest at exposed sites for L. digitata(25.77 g
DW m−2 day−1) owing to greaterrates ofdislodgement. Scaled annu-
ally, L. digitataproduces9.4 kgDW m−2 year−1 of detritus on exposed
and 5.96 kg DW m−2 year−1 on moderately exposed shores and S. la-
tissimaproduces 1.9 kg DW m−2 year−1 of detritus on moderately ex-
posedshores.Alth o u g hwed i d n o t m e a s u r e d e t r i t a l p r o d u c tiond u r in g 
every month of the year and may have missed smaller- scale patterns
associated with storms, we have captured the seasonal dynamics and
larger-scalepatternsoftheseprocesses.However,thelackofreliable
spatial ex tent data for either species , particularly within intertidal and
shallow subtidalhabitat sintheUKandIreland, makes scaling-upto
whole coastlines and seascapes challenging. Even so, the total contri-
but io nofintert idalkelpstandstolocalan dregion aldetritalp oo lsand
coastalcarbon cycles is likely to besignificant. A major knowledge
gap relates to the ultimate fate of this detrital material, in terms of
howquicklyit isconsumedandremineralized,whetherit subsidizes
receiverhabitats,andwhether anykelp-derivedcarbonis storedin
sinkhabitatsformeaningfultimescales.
In conclus ion, we have shown that i ntertidal kelp b eds con-
stitute a significant carbon flux and are major contributors to
coastal productivity and detritus production, highlighting the
ne ed fo rt h es eh abi tat st ob einco rpora tedintoec os yst emmod els.
Previous e stimations of m acroalgal co ntribution s to coastal ca r-
bon cycleshavegenerallyfocusedonintertidal fucoidsand sub-
tidal populations of kelp (Pessarrodona et al., 2022). It is important
tonote,however,thattherateestimatespresentedherewereob-
tained from alimited numberof sites withina regionwheresuch
informationisveryscarce(Schoenrocketal.,2020, 2021).For L.
digitata, population densities were at the higher end of previous
estimat es, and individu al size far exceeded pr eviously repor ted
values, resulting in very high estimates of productivity and detrit al
production. In addition, S. latissima typically dominates sheltered
shorelines that were not the focus of the current study, so that
the contr ibution of this sp ecies to region al carbon bud gets and
foodwebsis probablyevengreaterthansuggestedhere.Fur ther
mensurative studies are needed across greater spatial scales, to
incorporate multiple L. digitata and S. latissima populations and a
wider range of environmental conditions. Improving our knowl-
edgeoftherolethesehabitatsplayincoastalandglobalcyclesis
critical to understanding climate- driven change and implementing
management plans with a climate- change mitigation perspective
(Duarte, 2017 ).
AUTHOR CONTRIBUTIONS
Abby R. Gilson: Conceptualization (lead); data curation (lead);
formal analysis (lead); investigation (lead); methodology (lead);
visualization(lead);writing–originaldraft(lead);writing–review
and editing (lead). Dan A. Smale:Conceptualization(supporting);
formal analysis (supporting); methodology (supporting); supervi-
sion(supporting); visualization(supporting); writing–reviewand
editing (supporting). Michael T. Burrows:Conceptualization(sup-
porting); formal analysis (supporting); methodology (supporting);
supervision (supporting); visualization (supporting); writing – re-
view and editing (supporting). Lydia J. White:Form ala na l ys is(sup-
porting); investigation (supporting); methodology (supporting);
visualization (supporting); writing –review and editing (support-
ing). Nessa E. O'Connor: Conceptualization (supporting);formal
analysis (supporting); funding acquisition (lead); methodology
(supporting);supervision(lead);visualization(supporting);writing
–reviewandediting(supporting).
ACKNOWLEDGMENTS
We would like to tha nk Conn Murray for h is invaluable hel p in
the field. This PhD was completed as part of a PhD studentship
funded by the Department for Economy Northern Ireland and
in part by t he Natural Envir onmental Res earch Council a nd the
DepartmentforEnvironment,Food,andRuralAffairs(grantnum-
berNE/L003279/1,MarineEcosystemsResearchProgramme).D.
Smale wassuppor ted bya UKRIFutureLeadersFellowship(MR/
S032827/1).

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CONFLICT OF INTEREST STATEMENT
The authors have no conflict of interest to declare.
DATA AVAIL AB ILI T Y STAT E MEN T
All data is av ailable from th e British Ocean ographic Data C entre.
DOI: https://doi.org/10.5285/bb7366a9-e053-6c86abc0cea1.
ORCID
Abby R. Gilson https://orcid.org/0000-0003-4607-1376
Lydia J. White https://orcid.org/0000-0002-7531-5168
Michael T. Burrows https://orcid.org/0000-0003-4620-5899
Dan A. Smale https://orcid.org/0000-0003-4157-541X
Nessa E. O’Connor https://orcid.org/0000-0002-3133-0913
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SUPPORTING INFORMATION
Additional supporting information can be found online in the
Suppor tingInformationsectionattheendofthisarticle.
How to cite this article: Gilson,A.R.,White,L.J.,Burrows,
M.T.,Smale,D.A.,&O’Connor,N.E.(2023).Seasonaland
spatialvariabilit yinratesofprimar yproductionanddetritus
releasebyintertidalstandsofLaminaria digitata and
Saccharina latissima on wave- exposed shores in the
northeastAtlantic.Ecology and Evolution, 13, e10146 . h t t p s: //
doi.org/10.1002/ece3.10146

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APPENDIX
METHODS TO QUANTIFY POTENTIAL ABIOTIC AND BIOTIC
FACTORS AFFECTING KELP PRODUCTION AND DETRITAL
PRODUCTION
Toidentify the biotic factors thatmayaffectkelp production and
breakdownandtotestwhethertheseeffectsdifferedamongdomi-
nant kelp species, 15 individuals of Lamin aria digitata and Saccharina
latissimaat e a chs i t ewe r e surve y e dfo r t h epre s e n c eof g r aze r s , w ith
grazeridentityanddensityperkelpindividualrecorded.Thedistal
partofthebladesofeachindividualkelpwasthenplacedbetween
two sheets of plexiglass and photographed. Only the distal 1/3rd
ofthe kelp individual was measured becauseerosion isknown to
occurpri ma ril yint he di sta lp or t io no ft hebladean dg razingand ep -
iphyticalgalcoverwereobservedtobeconcentratedinthisregion
(Krumhansl&Scheibling,2011).Distalareagr azed(est imatedusing
perforationsofthebladeonl y)andpercent ag ee pi ph yticalg alcover
werethen calculated bydividingthetot alarea bythearea grazed
andtheareacover edbyepiphyticalgae ,re spectively,usingImageJ.
Toi dentify abi otic factor s that may affec t kelp produc tion and
breakdown,temperature (°C)andlight(lumens ft2) were recorded
every15 minandaveragedforeachsiteduringeachsamplingperiod
using data loggers (n = 8; HOBO temperature/light weatherproof
Pendant data Logger 16k, Onset). Meanand monthly temperature
and light and daily cumulative irradiance were then calculated for
each site du ring each sa mpling per iod. As log gers were pl aced in-
tertidally, estimates include periods of low tide emersion and there-
foreairtemperature.Datawerenotavailable forsamplingperiod6
(August2017)owingtoadverse weatherconditions preventingthe
collection or loss of the loggers.
FIGURE A1 Laminaria digitata and Sacharina latissimakelpbedslocatedat(a)Bally whoriskeyPointand(b)RinmorePointinCo.Donegal,
Ireland.
(a) (b)

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FIGURE A2 Monthlymaximumandmeantemperature(aandb,respectively;°C),lightintensity(candd,respectively;lumensft2), and
daily cumulative irradiance (e; lumens ft2).Datawerebasedontwositesattwodifferentlevelsofwaveexposure(exposedandmoderately
exposed; n = 2perlevelofwaveexposure)inCo.Donegal,Ireland.

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FIGURE A3 Mean(±1 SE)totalgrazerabundance(perkelpindividual),distalareagrazed(%perkelpindividual),andepiphyticalgalcover
(per individual) of Laminaria digitata (a, c, and e, respec tively) and Saccharina latissima(b,d,andf,respectively).Datawerebasedontwositesat
two different levels of wave exposure (exposed and moderately exposed; n = 2perlevelofwaveexposure)inCo.Donegal,Ireland.n = 1 0 – 3 7 .