Submitted 25 August 2016Accepted 12 December 2016Published 25 January 2017

Corresponding authorJohan Ekloumlf johaneklofsuse

Academic editorRichard Taylor

Additional Information andDeclarations can be found onpage 11

DOI 107717peerj2906

Copyright2017 Ekloumlf et al

Distributed underCreative Commons CC-BY 40

OPEN ACCESS

Size matters relationships between bodysize and body mass of common coastalaquatic invertebrates in the Baltic SeaJohan Ekloumlf1 Aringsa Austin1 Ulf Bergstroumlm2 Serena Donadi13Britas DHK Eriksson4 Joakim Hansen3 and Goumlran Sundblad5

1Department of Ecology Environment and Plant Sciences (DEEP) Stockholm University Stockholm Sweden2Department of Aquatic Resources Swedish University of Agricultural Sciences Oumlregrund Sweden3Baltic Sea Centre Stockholm University Stockholm Sweden4Groningen Institute for Evolutionary Life-Sciences GELIFES University of Groningen GroningenNetherlands

5Aquabiota Water Research Stockholm Sweden

ABSTRACTBackground Organism biomass is one of the most important variables in ecologicalstudiesmaking biomass estimations one of themost common laboratory tasks Biomassof small macroinvertebrates is usually estimated as dry mass or ash-free dry mass(hereafter lsquoDMrsquo vs lsquoAFDMrsquo) per sample a laborious and time consuming process thatoften can be speeded up using easily measured and reliable proxy variables like bodysize or wet (fresh) mass Another common way of estimating AFDM (one of the mostaccurate but also time-consuming estimates of biologically active tissue mass) is the useof AFDMDM ratios as conversion factors So far however these ratios typically ignorethe possibility that the relative mass of biologically active vs non-active support tissue(eg protective exoskeleton or shell)mdashand therefore also AFDMDM ratiosmdashmaychange with body size as previously shown for taxa like spiders vertebrates and treesMethods We collected aquatic epibenthic macroinvertebrates (gt1 mm) in 32 shallowbays along a 360 km stretch of the Swedish coast along the Baltic Sea one of the largestbrackish water bodies on Earth We then estimated statistical relationships betweenthe body size (length or height in mm) body dry mass and ash-free dry mass for 14of the most common taxa five gastropods three bivalves three crustaceans and threeinsect larvae Finally we statistically estimated the potential influence of body size onthe AFDMDM ratio per taxonResults For most taxa non-linear regression models describing the power relationshipbetween body size and (i)DMand (ii) AFDMfit the datawell (as indicated by lowSE andhigh R2) Moreover for more than half of the taxa studied (including the vast majorityof the shelled molluscs) body size had a negative influence on organism AFDMDMratiosDiscussion The good fit of themodelled power relationships suggests that the constantsreported here can be used to quickly estimate organism dry- and ash-free dry massbased on body size thereby freeing up considerable work resources However theconsiderable differences in constants between taxa emphasize the need for taxon-specific relationships and the potential dangers associated with ignoring body sizeThe negative influence of body size on the AFDMDM ratio found in a majority ofthe molluscs could be caused by increasingly thicker shells with organism age andor

How to cite this article Ekloumlf et al (2017) Size matters relationships between body size and body mass of common coastal aquatic in-vertebrates in the Baltic Sea PeerJ 5e2906 DOI 107717peerj2906

spawning-induced loss of biologically active tissue in adults Consequently futurestudies utilizing AFDMDM (and presumably also AFDMwet mass) ratios shouldcarefully assess the potential influence of body size to ensure more reliable estimates oforganism body mass

Subjects Aquaculture Fisheries and Fish Science Biodiversity Ecology Marine Biology ZoologyKeywords Estuary Biometry Infauna Submerged aquatic vegetation Isometric scalingLengthweight relationship Epifauna Allometry Seagrass Weight

INTRODUCTIONOrganism biomass is inarguably one of the more important variables in ecology playinga central role in studies ranging from ecophysiology and community and food webregulation to whole-ecosystem metabolism (eg Enquist amp Niklas 2001 Gruner et al2008 Perez-Harguindeguy et al 2013) As a consequence to accurately estimate organismbiomass constitutes one of the most common and important tasks in ecological studies

Small invertebrates retained on 05ndash1 mm sieves (hereafter lsquomacrofaunarsquo) make up amajor part of animal density diversity and biomass in many ecosystems eg insects andarachnids in terrestrial ecosystems epibenthic aquatic crustaceans echinoderms and mol-luscs in stands of aquatic vegetation and infaunal (sediment-dwelling) worms crustaceansand molluscs in marine sediments Macrofauna biomass is typically reported as dry- orash-free dry mass per unit area (eg g per m2) which requires observers to repeatedlyidentify sort dry and weigh individual or pooled organisms a time-consuming expensiveand tedious process Many studies have shown that more easily measured proxy variablesscale predictably with dry mass and therefore can be used to speed up biomass estimationseg wet (fresh) mass (Brey Rumohr amp Ankar 1988 Ricciardi amp Bourget 1998 Brey et al2010) and body size based on either exact length measurement (Smock 1980 FrithsenRudnick amp Doering 1986 Sabo Bastow amp Power 2002) or retention on sieves of certainmesh sizes (Widbom 1984 Edgar 1990 Casagranda amp Boudouresque 2002) While wetmass can be a very good proxy (see eg Ricciardi amp Bourget 1998) wemdashas others beforemdashargue that body size (eg length) holds several advantages and lacks several disadvantagesassociated with wet mass estimations First ecological theory supported by empirical datasuggest body mass scales predictably with length in the form of power relations (Smock1980 Sabo Bastow amp Power 2002) Second while freezingthawing and fixation in con-servation liquids (eg EtOH or formalin) can affect both organism wet mass (Howmiller1972 Mason Lewis amp Weber 1983 Leuven Brock amp van Druten 1985) and length(Hjoumlrleifsson amp Klein-MacPhee 1992 Kapiris Miliou amp Moraitou-Apostolopoulou 1997)wet mass estimations are also very sensitive to exactly how specimens are blotted cen-trifuged (to remove excess water) and exposed to air and light before and during weighing(Howmiller 1972Mason Lewis amp Weber 1983 Leuven Brock amp van Druten 1985) As sizeestimations do not require blotting they are less sensitive to observer error and also faster toperform Third body size (eg length or height) estimations canmore easily be automated

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 214

using eg image analysis software (Paavo et al 2008 Mallard Le Bourlot amp Tully 2013)to rapidly process multiple individuals at a time

In benthic ecology ash-free dry mass (hereafter lsquoAFDMrsquo in the older literaturesometimes called lsquoash-free dry weightrsquo or simply lsquoAFDWrsquo) is often regarded as the mostaccurate predictor of macrofauna biomass as it only includes biologically active tissueSince AFDM estimations require the incineration of dried samples in a furnace at hightemperature adding considerable time and costs to analyses many studies have reportedhowAFDM scales with estimations of wet- and drymass usually in the formof simple ratiosas lsquoconversion factorsrsquo (eg AFDMDM in ) (Rumohr Brey amp Ankar 1987 Ricciardiamp Bourget 1998) However these ratios typically ignore the possibility that the relativemass of biologically active vs non-active support tissue (eg protective exoskeleton orshell)mdashand therefore the AFDMDM ratiomdashmay change with macrofauna body size aspreviously shown for disparate taxa like spiders (Andersen 1979) vertebrates (Miller ampBirchard 2005) and trees (Niklas 1995) This issue is important not only for obtainingaccurate biomass conversions and estimations but also for understanding how organismalinvestment in one type of structure may limit or constrain investment in other structuresacross ontogenetic development stages (Lease amp Wolf 2010)

Here we estimate and report relationships between body size dry mass and ash-free drymass for 14 of the most common aquatic epibenthic invertebrate taxa found in shallowvegetated habitats of the central Baltic Sea one of the largest brackish water bodies on EarthFor each taxon we also assess whether the ash-free dry massdry mass ratio changes withbody size Our aim is to provide simple yet reliable size-based relationships that can beused to rapidly estimate organism body mass and ultimately biomass per sample

METHODSStudy areaThe Baltic Sea is a 415000 km2 large marginal sea situated in northern Europe (53ndash66N10ndash30E) A main feature is the presence of strong horizontal and vertical gradients insalinity temperature and oxygen that also undergo considerable temporal (eg seasonal)fluctuations (Voipio 1981) The Baltic Sea is evolutionary very young (ca 6000 years) andthe shallow coastal areas have since the last glaciation been colonized by amixture ofmarinefreshwater and brackish organisms including crustaceans gastropods bivalves poly-chaetes hirudineans nemerteans and insect larvae (Hansen Wikstroumlm amp Kautsky 2008)As many marine and freshwater organisms in the Baltic Sea live near their physiologicaltolerance limits they grow slower and smaller than in their original environment eg theblue mussel Mytilus edulis (Tedengren amp Kautsky 1986) As a consequence their sizerangesmdashbut also sizemass relationships and potentially AFDMDM ratiosmdashcould differfrom those reported for conspecifics in marine or freshwater areas (Rumohr Brey amp Ankar1987) An estimate of the effect of salinity on sizemass or DMAFDM relationship wasbeyond the scope of our study but our results could be compared to relationships inmarine populations of the same taxa if sampled and measured in the same way

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 314

Field samplingDuring summer (MayndashAug) 2014 we collected aquatic invertebrate macrofauna (gt1 mm)in 32 shallow bays situated along a 360 km stretch of the central Swedish Baltic Sea coastline(Fig 1) The salinity in the area is generally low (ca 5ndash7 psu) but fluctuates strongly withfreshwater runoff and upwelling events In each bay a snorkeler sampled submerged aquaticvegetation and epibenthic macrofauna in 3ndash8 randomly selected stations (gt30 m apart) bygently placing a 20 times 20 cm frame (with a 1 mm-mesh bag attached) on the sea bed andcollecting all organisms (aquatic vegetation and associated invertebrates) found above oron top of the sediment surface The bag content was immediately transferred to a plasticbag which was kept cold on ice until frozen (minus20 C) in most cases within 1ndash3 h

Body size estimationsFollowing thawing in room temperature we identified intact invertebrate organisms to thehighest taxonomic resolution feasible using standard literature For the 14 most commontaxa we then selected and measured the body size of 12ndash459 individuals per taxa (3220individuals in total) chosen to capture the full range of body sizes found across the 32 baysThe taxa included five gastropods (Theodoxus fluviatilis Hydrobia spp Radix balthicaPotamopyrgus antipodarum Bithynia tentaculata) three bivalves (Mytilus edulis Limecola(Macoma)) balthica and Cardidae spp (numerically dominated by Parvicardiumhauniense) three crustaceans (Amphibalanus improvisus Idotea spp Gammarus spp) andthree insects (larval stages of Chironomidae spp Agraylea spp and Phryganeidae spp) (seealso Table 1) Body size (to the nearest 1mm)wasmeasured (based on standard proceduresHayward amp Ryland 1995) as (i) gastropod height along the central shell axis (ii) bivalvelength from anterior to posterior side (iii) total length of Gammarus and Idotea spp fromtip of rostrum to last urosome (iv) body width for Amphibalanus improvisus and (v) totallength of insect larvae from end of head to last segment A higher size accuracy is definitelypossible (eg to 01 or 001 mm using calipers or stereo lenses) but as most studiesutilizing this type of data (including ours) will depend on 1000s of length measurementsthe accuracy chosen was a realistic trade-off between time and precision

Estimations of dry- and ash-free dry massFollowing size estimations the measured individuals were transferred to pre-dried and-weighed (nearest 00001 g) porcelain crucibles For most size classes (except for very largeand rare individuals)multiple individuals were typically pooled into the same crucible Thisstep underestimates actual variability in bodymass between individuals butwas necessary asthe low individual body masses (particularly AFDM) were near or below the reliabledetection limit of the scale We included multiple estimations of the same sizes so that thenumber of biomass estimations (N ) ranged from 10 to 42 per taxa Samples were then driedat 60 C for gt48 h (until constantmass) and cooled to room temperature in a desiccator be-fore weighing To estimate ash-free drymass the crucibles were then transferred to amufflefurnace incinerated (550 C for 3 h) cooled and weighed again Ash-free dry mass wascalculated as dry mass minus ash mass

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 414

Table 1 Results of regression analyses estimating (i) the non-linear power relationship between body size and dry mass (DM) and (ii) ash-free dry mass (AFDM)(iii) the meanplusmn 1SE AFDMDM ratio (in ) and (iv) the linear relationship between body size and AFDMDM ratio (in ) for 14 macroinvertebrate taxa in shallowcoastal areas of the Baltic Sea Letters within parentheses after taxa names denote classes

Body size vs DM Body size vs AFDM AFDMDM Body size vs AFDMDM

Taxon N αplusmn SE βplusmn SE R2 αplusmn SE βplusmn SE R2 Meanplusmn 1 SE Interceptplusmn SE Slopeplusmn SE R2

Bithynia tentaculataL (G)

25 0598plusmn 0484ns 2117plusmn 0351 0847 0479plusmn 0511ns 136plusmn 0472 0668 19133plusmn 2207 33162plusmn 3878 minus191plusmn 0452 0424

Hydrobia spp (G) 24 0239plusmn 0041 2134plusmn 0095 0952 0079plusmn 0029 1441plusmn 022 0758 13737plusmn 1155 19791plusmn 2855 minus0633plusmn 0715 0155

Potamopyrgusantipodarum Gray (G)

17 0479plusmn 0511ns 1360plusmn 0472 0919 0021plusmn 0012ns 2447plusmn 0395 0898 16051plusmn 1399 6063plusmn 4616ns 2653plusmn 1180 0202

Radix balthica L (G) 20 0137plusmn 0035 2355plusmn 0115 0956 0046plusmn 0018 2119plusmn 0177 0906 27087plusmn 2233 35338plusmn 3558 minus1794plusmn 0650 0258

Theodoxus fluviatilisL (G)

29 0221plusmn 0065 2683plusmn 0148 09492 0015plusmn 0006 2915plusmn 0194 0912 13044plusmn 1083 1852plusmn 2396 minus0242plusmn 0494 0159

Cardidae spp (B) 33 0134plusmn 0094ns 2848plusmn 0347 0924 0014plusmn 0013ns 2806plusmn 0486 0879 12358plusmn 0852 18075plusmn 1468 minus0429plusmn 0325 0364

Limecola balthica L (B) 18 0069plusmn 0024 2820plusmn 0134 0991 0001plusmn 0002ns 3479plusmn 0673 092 12717plusmn 1934 21429plusmn 298 minus0264plusmn 0372 0383

Mytilus edulis L (B) 24 0030plusmn 0015 2933plusmn 0153 0991 0006plusmn 0003 2844plusmn 0147 0978 14189plusmn 0504 13162plusmn 1044 0078plusmn 0069ns 0011

Amphibalanusimprovisus Darwin (C)

13 0314plusmn 0205ns 2515plusmn 0289 0976 0036plusmn 0022ns 2289plusmn 0276 0961 8939plusmn 0550 11044plusmn 1064 minus0397plusmn 0179 0246

Gammarus spp (C) 37 0047plusmn 0032ns 2111plusmn 0265 0926 0033plusmn 0028ns 205plusmn 032 0863 58966plusmn 1519 63062plusmn 2616 minus0389plusmn 0307ns 0017

Idothea spp (C) 42 0001plusmn 0001ns 3592plusmn 0200 0949 0001plusmn 0001ns 3850plusmn 0249 0919 61505plusmn 1659 66183plusmn 3457 minus0550plusmn 0358ns 0032

Agraylea spp (I) 13 0001plusmn 0002ns 3410plusmn 0721 0820 0001plusmn 0002ns 3432plusmn 0769 0833 85967plusmn 3769 88893plusmn 7725 0570plusmn 1277ns minus0097

Chironomidae spp (I) 38 0014plusmn 0016ns 1383plusmn 0290 0600 0008plusmn 0006ns 1544plusmn 0321 0533 79307plusmn 2643 78633plusmn 6947 0070plusmn 0688ns minus0027

Phryganeidae spp (I) 10 0001plusmn 0001ns 3176plusmn 0649 0746 0001plusmn 0001ns 3207plusmn 0611 0789 91851plusmn 2137 8664plusmn 3558 0382plusmn 0185ns 0290

NotesG Gastropoda B Bivalvia C Crustacea I Insecta (larvae) α and β normalization and scaling constant for power equations respectively

nsplt 005plt 005plt 001plt 0001Values in bold mark those significant (at α= 005) Note R2 were derived from linear logndashlog models

Ekloumlfetal(2017)PeerJDOI107717peerj2906

514

Figure 1 Maps of Scandinavia (small image) and the sampling area Filled circles mark the position ofthe 32 sampled bays Numbers along the x- and y-axis are longitude and latitude respectively

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 614

Statistical analysesWe estimated taxon-specific body sizebody mass relationship using non-linear regressionin the form of the power equation

body mass=αtimes sizeβ

where body mass is the individual mass (mg DM or AFDM) size is the body size (length-height in mm) α is a normalization constant and β is the scaling constant Body masstypically scales with size in a power relationship and initial data exploration showed thatpower equations provided a superior fit compared to linear log or exponential relationshipsAs regression coefficients (R2) are an inadequate measure of fit for non-linear regressionmodels (Spiess amp Neumeyer 2010) we report SE for α and β However for the sake ofsimplicity we also estimated the linear logndashlog relationship between body size and biomassand report the R2 for those models (see eg Lease amp Wolf 2010)

For each taxonwe also calculated themean (plusmn1 SE)AFDMDMratio (in) a commonlyused conversion factor in macroinvertebrate studies (see eg Ricciardi amp Bourget 1998)We then used linear regression to test whether body size (in mm) affected the AFDMDMratio Prior to analyses we checked assumptions of normality (by plotting predicted vsobserved quantiles) and homoscedasticity (by plotting predicted vs observed residuals)All analyses were conducted in R v 323 (R Core Team 2016)

RESULTSRelationships between body size and individual biomassThe relationships between body size (mm) individual dry mass (mg DM) and ash-free drymass (mg AFDM) for all 14 taxa are displayed in Figs 2Andash2H and the parameters (and theirfit) are presented in Table 1 For most of the taxa body size was a very good predictor ofindividualDM as demonstrated by low SE andR2 near 1 Themodel fits were slightly poorerfor the three insect taxa (R2

= 060ndash082) and the gastropodBithynia tentaculata (R2= 085)

than for the other ten taxa For amajority (12 out of 14) of the taxa the scaling constants (β)were well above 2 (2110ndash3590) The exceptions were the small gastropod Potamopyrgusantipodarum and chironomid larvae which had constants closer to 1 (β = 1368 and 1383respectively)

Body size was also a very good predictor of AFDM even though model fits (based onSE and R2) were slightly poorer than for DM (Table 1) Just as for DM relationships themodel fits (based on SE and R2) were best for gastropods molluscs and crustaceans Thescaling constants (β) were for most taxa quite similar to those reported for the DMrelationships with the exception of a higher constant for P antipodarum (β = 2447) anda lower constant for Bithynia tentaculata (β = 1360)

Influence of organism body size on AFDMDM ratiosThe AFDMDM ratios (mean plusmn SE) per taxa are also presented in Table 1 As expectedthere were consistent differences between the four major taxonomic groups studied withlow AFDM content in bivalves and gastropods (12ndash27) whorsquos calcium carbonate shell

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 714

0

30

60

90

120

mg

DM

Theodoxus fluviatilisBithynia tentaculata

Radix balthica

Potamopyrgus antipodarum

Gastropoda

0

5

10

15

20

mg

AF

DM

10

20

30

40

50

1 2 3 4 5 6 7 8 9 10 11 12

AF

DM

D

M (

)

0

100

200

300

400

500

Cardidae sppLimecola (Macoma) balthicaMytilus edulis

Bivalvia

0

20

40

60

10

20

30

0 4 8 12 16 20 24 28

0

50

100

Amphibalanus improvisusGammarus sppIdothea spp

Crustacea

0

5

10

15

20

20

40

60

80

2 6 10 14 18 22

Length (mm)

0

5

10

Phryganeidae sppAgraylea sppChironomidae spp

Insecta (larvae)

0

4

8

12

20

40

60

80

100

4 8 12 16 20 24 28

Hydrobia spp

a) b) c) d)

e) f) g) h)

i) j) k) l)

Figure 2 Best-fitting relationships between body size (length or height see lsquoMethodsrsquo) and (AndashD) dry mass (mg DM) (EndashH) ash-free dry mass(mg AFDM) and (IndashL) AFDMDM ratio ( AFDM) for 14 taxamdashfive gastropods three bivalves three crustaceans and three insect larvaemdashsampled in coastal areas of the central Baltic Sea For model parameters and estimates of fit see Table 1

makes up the major part of whole-body biomass to higher AFDM content in chitin-shelledcrustaceans (ca 60) and the highest content in insect larvae (86ndash92)

Results of simple linear regression showed that formore than half (8 out of 14) of the taxasurveyed body size clearly affected the AFDMDM ratio (Table 1 and Figs 2Indash2L) For fourout of five gastropods two out of three bivalves as well as the sessile calcite-shelled crus-taceanAmphibalanus improvisus theAFDMDMratio decreased linearlywith body size Forthe small gastropod Potamopyrgus antipodarum body size instead had a positive influence

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 814

on AFDMDM However the P antipodarum size range was very narrow (2ndash4 mm) andthe intercept was not different from 0 (Table 1) suggesting a relatively poor model fitMoreover there was no size effect found in the bluemusselMytilus edulis (Table 1) Finallyin contrast to the size effects found for most of the hard-shelled molluscs there was noinfluence of body size on AFDMDM in any of the chitin-shelled crustaceans or insectlarvae (Table 1 and Figs 2Indash2L)

DISCUSSIONEstimating organism biomass is one of the most common important but also resource-consuming tasks in ecological work particularly when it comes to small-bodied highlyabundant and diverse macroscopic invertebrates Many previous studies have shown thatmore easily measured variables like invertebrate wet (fresh) mass (eg Ricciardi amp Bourget1998) or body size (eg Smock 1980) can be used as proxies to reliably predict both the dry-and ash-free dry body mass thereby simplifying and speeding up biomass estimationsHere we first complement this literature by reporting how body mass scales with body sizefor 14 of the most common epibenthic invertebrate taxa found in shallow coastal areas ofthe Baltic Sea Moreover we demonstrate that for a majority of the studied molluscs theratio between organism dry- and ash-free dry massmdashan often-used conversion factor (egRumohr Brey amp Ankar 1987 Ricciardi amp Bourget 1998)mdashdecreases predictably with bodysize Thus our results can be used to quickly estimate the biologically active biomass ofindividual organisms based on their size and when combined with density data accuratelyestimate biomass per unit area

Body size as a proxy for dry- and ash-free dry massFor a majority of the studied taxa body size was a good predictor of both dry mass and ash-free drymass Themodel fits were slightly poorer for ash-free drymass (AFDM)most likelya consequence of the fact that even thoughmultiple individuals of the same sizewere pooledthe low individual AFDM of many organisms (in the vicinity of 1 mg) challenged the accu-racy of the scale Comparisons between the 14 taxa studied (Table 1) show that particularlywithin the gastropods and crustaceans the scaling (β) constants differ quite substantiallybetween taxa (see the different slopes in Fig 2 and β coefficients in Table 1) These differ-ences emphasize the need for taxon-specific relationships to accurately predict biomassand the potential dangers in either ignoring body size or substituting relationships betweentaxa Consequently our power equations (Table 1) can be used in a simple yet reliable wayto estimate organism dry- or ash-free dry mass based on standard body size measurementsFuture studies should ideally also assess how these relationships vary in time and space(eg over seasons) for even more accurate biomass estimations Size-based biomassestimations are likely to speed up laboratory work considerably for example Casagrandaamp Boudouresque (2002) showed that sieve-based size estimations speeded up estimations ofbody biomass of the gastropodHydrobia ventricosa by 20ndash30 times Consequently our size-based estimations of invertebrate biomass are likely to free up considerable work resources(time man-power money) that can be used to eg collect and process more samples

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 914

The influence of body size on AFDMDM ratiosFor most of the taxa with a calcium-carbonate (molluscs) or calcite shell (the barnacleAmphibalanus improvisus) we found a significant negative influence of body size on theAFDMDM ratio a commonly reported and often-used conversion factor in macrofaunastudies (eg Rumohr Brey amp Ankar 1987 Ricciardi amp Bourget 1998) In other words theproportional mass of biologically active vs non-active tissue (shell hard mouth parts etc)decreased with body size There are at least two possible and complementary explanationsfor this relationship First while the rate of growth in length of mollusc shells typicallydecreases with age new shell layers are consistently added on a yearly basis (Negus 1966)This results in increasingly thicker and therefore disproportionally heavier shells withmussel length and a higher shelltissue mass ratio Second our sampling was conductedduring summer a season when a majority of adult molluscs (here represented by thelarger individuals per taxa) most likely had spawned and temporarily lost a considerableproportion of their biologically active tissue (Kautsky 1982) The slopes of the significantregressions (Table 1 median =minus126) suggest that failing to incorporate the potentialinfluence of body size can strongly reduce the accuracy of AFDM estimations based ondry mass (and presumably also wet mass) particularly if there is considerable variability inbody size in the samples The somewhat surprising lack of size influence in the commonblue musselMytilus edulis was not investigated in detail but could be caused by (i) the lackof small shell-crushing mussel predators in the area (eg crabs) who otherwise are knownto trigger thicker mussel shells (Freeman 2007) andor (ii) the relatively low salinitywhich causes the small osmotically stressed M edulis to invest considerably more energyinto osmosis and soft tissue production than in thicker shells (Kautsky Johannesson ampTedengren 1990)

In contrast to the results formolluscs therewas no size effect onAFDMDMratios for thechitin-shelled insects and crustaceans These results fit well with those reported in previousstudies for example of terrestrial insects for which exoskeletal chitin scales isometrically(11) with body size (Lease amp Wolf 2010) In summary our results suggest that body sizecan play an important but hitherto underestimated role when estimating organism AFDMbased on dry (and possibly wet) mass particularly for shelled molluscs

CONCLUSIONSUsing samples of epibenthicmacroinvertebrates collected in 32 shallow bays along a 360 kmstretch of the Swedish Baltic Sea coast we show that for 14 of themost commonmacrofaunataxa organism body size scales predictably with individual dry mass and ash-free dry massin the form of power relations The good model fits suggest the taxon-specific equationsreported here can be used to predict individual biomass based on organism size therebyspeeding up estimations of macrofauna biomass Moreover for the vast majority of themolluscs studied we find a negative relationship between body size and AFDMDM ratioa commonly used conversion factor in macrofauna studies Consequently future studiesutilizing AFDMDM ratios should carefully assess the potential influence of body size andspatialndashtemporal variability to ensure reliable biomass estimations

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 1014

ACKNOWLEDGEMENTSWe acknowledge the field andor laboratory assistance of (in alphabetic order) T AmgrenE Anderberg F Ek P Jacobsson G Johansson C Joumlnander L Naumlslund O Pettersson Mvan Regteren S Skoglund E Svartgren V Thunell C Aringkerlund and M Aringkerman We thankthe water right owners around each study bay for facilitating the field sampling This studyis a product of project Plant-Fish (wwwplantfishse)

ADDITIONAL INFORMATION AND DECLARATIONS

FundingThis study was funded by Formas (grant 2013-1074) His Majesty Carl XVI GustafrsquosFoundation for Science and Education (grant HMK-2014-0002) the Baltic Sea 2020foundation (project lsquolsquoLevande kustrsquorsquo) Stockholm University Baltic Sea Centre (Askoumlgrants and support to MSc students) and in-kind support from Groningen University(Netherlands) to BDHK Eriksson The funders had no role in study design data collectionand analysis decision to publish or preparation of the manuscript

Grant DisclosuresThe following grant information was disclosed by the authorsFormas 2013-1074His Majesty Carl XVI Gustafrsquos Foundation for Science and Education HMK-2014-0002Baltic Sea 2020 foundationStockholm University Baltic Sea CentreGroningen University

Competing InterestsGoumlran Sundblad is an employee of AquaBiota Water Research His work in relation to thisstudy was fully funded by a grant from Formas the Swedish research council for sustainabledevelopment

Author Contributionsbull Johan Ekloumlf conceived and designed the experiments performed the experimentsanalyzed the data contributed reagentsmaterialsanalysis tools wrote the paperprepared figures andor tablesbull Aringsa Austin Serena Donadi Britas DHK Eriksson and Goumlran Sundblad performed theexperiments contributed reagentsmaterialsanalysis tools reviewed drafts of the paperbull Ulf Bergstroumlm and Joakim Hansen performed the experiments contributedreagentsmaterialsanalysis tools prepared figures andor tables reviewed drafts ofthe paper

Data AvailabilityThe following information was supplied regarding data availability

The raw data has been supplied as Data S1

Ekloumlf et al (2017) PeerJ DOI 107717peerj2906 1114

Supplemental InformationSupplemental information for this article can be found online at httpdxdoiorg107717peerj2906supplemental-information

REFERENCESAndersen SO 1979 Biochemistry of insect cuticle Annual Review of Entomology

2429ndash59 DOI 101146annureven24010179000333Brey T Muller-Wiegmann C Zittier ZMC HagenW 2010 Body composition in

aquatic organismsmdasha global data bank of relationships between mass elementalcomposition and energy content Journal of Sea Research 64(3)334ndash340DOI 101016jseares201005002

Brey T Rumohr H Ankar S 1988 Energy content of macrobenthic invertebratesgeneral conversion factors from weight to energy Journal of Experimental MarineBiology and Ecology 117(3)271ndash278 DOI 1010160022-0981(88)90062-7

Casagranda C Boudouresque CF 2002 A sieving method for rapid determination ofsize-frequency distribution of small gastropods Example of the mud snail Hydrobiaventrosa Hydrobiologia 485(1)143ndash152 DOI 101023A1021371308753

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 137(3)195ndash214 DOI 1010160022-0981(90)90185-F

Enquist BJ Niklas KJ 2001 Invariant scaling relations across tree-dominated communi-ties Nature 410655ndash660 DOI 10103835070500

Freeman AS 2007 Specificity of induced defenses inMytilus edulis and asymmetricalpredator deterrenceMarine Ecology Progress Series 334145ndash153DOI 103354meps334145

Frithsen JB Rudnick DT Doering PH 1986 The determination of fresh organiccarbon weight from formaldehyde preserved macrofaunal samples Hydrobiologia133(3)203ndash208 DOI 101007BF00005591

Gruner DS Smith JE Seabloom EW Sandin SA Ngai JT Hillebrand H HarpoleWSElser JJ Cleland EE BrackenMES Borer ET Bolker BM 2008 A cross-systemsynthesis of consumer and nutrient resource control on producer biomass EcologyLetters 11(7)740ndash755 DOI 101111j1461-0248200801192x

Hansen JPWikstroumlm SA Kautsky L 2008 Effects of water exchange and vegetation onthe macroinvertebrate fauna composition of shallow land-uplift bays in the BalticSea Estuarine Coastal and Shelf Science 77(3)535ndash547DOI 101016jecss200710013

Hayward PJ Ryland JS 1995Handbook of the marine fauna of North-West Europe NewYork Oxford University Press 800 pp

Hjoumlrleifsson E Klein-MacPhee G 1992 Estimation of live standard length of winterflounder Pleuronectes americanus larvae from formalin-preserved ethanol-preserved and frozen specimensMarine Ecology Progress Series 8213ndash19DOI 103354meps082013

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Howmiller RP 1972 Effects of preservatives on weights of some common macrobenthicinvertebrates Transactions of the American Fisheries Society 101(4)743ndash746DOI 1015771548-8659(1972)101lt743EOPOWOgt20CO2

Kapiris K Miliou H Moraitou-ApostolopoulouM 1997 Effects of formaldehydepreservation on biometrical characters biomass and biochemical compositionof Acartia clausi (Copepoda Calanoida) Helgolander Meeresuntersuchungen51(1)95ndash106 DOI 101007BF02908757

Kautsky N 1982 Quantitative studies on gonad cycle fecundity reproductive outputand recruitment in a balticMytilus edulis populationMarine Biology 68(2)143ndash160DOI 101007BF00397601

Kautsky N Johannesson K TedengrenM 1990 Genotypic and phenotypic differencesbetween Baltic and North Sea populations ofMytilus edulis evaluated throughreciprocal transplantations I Growth and morphologyMarine Ecology ProgressSeries 59203ndash210 DOI 103354meps059203

Lease HMWolf BO 2010 Exoskeletal chitin scales isometrically with body size interrestrial insects Journal of Morphology 271(6)759ndash768 DOI 101002jmor10835

Leuven RSEW Brock TCM Van Druten HAM 1985 Effects of preservation on dry-and ash-free dry weight biomass of some common aquatic macro-invertebratesHydrobiologia 127(2)151ndash159 DOI 101007BF00004193

Mallard F Le Bourlot V Tully T 2013 An automated image analysis system to mea-sure and count organisms in laboratory microcosms PLOS ONE 8(5)e64387DOI 101371journalpone0064387

MasonWT Lewis PAWeber CI 1983 An evaluation of benthic macroinvertebratebiomass methodology Environmental Monitoring and Assessment 3(1)29ndash44DOI 101007BF00394030

Miller K Birchard GF 2005 Influence of body size on shell mass in the ornate boxturtle terrapene ornata Journal of Herpetology 39(1)158ndash161DOI 1016700022-1511(2005)039[0158IOBSOS]20CO2

Negus C 1966 A quantitative study of growth and production of unionid mussels in theRiver Thames at reading Journal of Animal Ecology 35513ndash532 DOI 1023072489

Niklas KJ 1995 Size-dependent allometry of tree height diameter and Truck-taperAnnals of Botany 75217ndash227 DOI 101006anbo19951015

Paavo B Ziegelmeyer A Lavric E Probert PK 2008Morphometric correlations andbody mass regressions for Armandia maculata Aglaophamus macroura (Poly-chaeta) and Zethalia zelandica (Gastropoda) New Zealand Journal of Marine andFreshwater Research 42(1)85ndash91 DOI 10108000288330809509938

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R Core Team 2016 R a language and environment for statistical computing Vienna RFoundation for Statistical Computing Available at httpswwwr-projectorg

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Smock LA 1980 Relationships between body size and biomass of aquatic insectsFreshwater Biology 10(4)375ndash383 DOI 101111j1365-24271980tb01211x

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TedengrenM Kautsky N 1986 Comparative study of the physiology and its probableeffect on size in Blue Mussels (Mytilus edulis L) from the North Sea and the North-ern Baltic Proper Ophelia 25(3)147ndash155 DOI 10108000785326198610429746

Voipio A 1981 The Baltic sea 1st edition Vol 30 Amsterdam Elsevier ScienceWidbom B 1984 Determination of average individual dry weights and ash-free

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