Disturbance mediates the effects of nutrients ondeveloping assemblages of epibiota

NELSON VALDIVIA,1* JARROD D. STEHBENS,2† BJÖRN HERMELINK,3

SEAN D. CONNELL,2 MARKUS MOLIS1 AND MARTIN WAHL4

1Section Seaweed Biology, Biologische Anstalt Helgoland, AlfredWegener Institute for Polar and MarineResearch, Marine Station, Kurpromenade 201, D-27498 Helgoland, Germany (E-mail:nelson.valdivia@awi.de), 2Southern Seas Ecology Laboratories, School of Earth and EnvironmentalSciences, University of Adelaide, Adelaide, South Australia, Australia, 3Leibniz Institute for FreshwaterEcology and Inland Fisheries, Berlin, and 4Leibniz Institute of Marine Science, Kiel, Germany

Abstract Local dynamics such as resource enhancement (e.g. nutrient supply) and stochastic events of destruc-tion (disturbances that provide new space) are hypothesized to counteractively affect species diversity andcomposition.We tested the independent and interactive effects of nutrients and disturbance on the development ofassemblages of epibiota attached to vertical surfaces in an oligotrophic system. Nutrient concentrations weremanipulated at three levels (ambient, medium and high) while disturbance was manipulated by removing biomassat seven frequencies (0¥, 2¥, 3¥, 4¥, 5¥, 7¥, 12¥). Nutrient and disturbance regimes had opposing effects ondiversity such that species richness increased with resource enhancement (nutrients) and declined withdisturbance. These results support the model that increased heterogeneity of distribution of limiting resourcesallows the coexistence of species with low and high resource requirements.

Key words: bottom-up, disturbance, diversity, marine, nutrient, top-down.

INTRODUCTION

Humans dominate the world’s coastlines through acombination of local stressors (e.g. nutrient inputand fishing) and global stressors (e.g. climate change)(Vitousek et al. 1997; Tilman et al. 2001). Althoughthese concerns have prompted considerable invest-ment into understanding the effects of nutrient supplyand disturbance (for reviews see Mackey & Currie2001; Mittelbach et al. 2001; Rajaniemi 2003; Sheil& Burslem 2003), the simultaneous manipulation ofboth factors is relatively rare (but see Worm et al.2002; Austen & Widdicombe 2006; Jara et al. 2006;Svensson et al. 2007).

Elevated nutrient supply can increase or decreasespecies diversity (reviewed by Waide et al. 1999). Fer-tilizations of aquatic systems can result in an increaseof diversity in nutrient-limited systems (e.g. Pringle1990; Hall et al. 2000; Bracken & Nielsen 2004). Oneexplanation is that local nutrient enhancement in oli-gotrophic systems increases spatial or temporal hetero-geneity of the distribution of the limiting resource, andtherefore allows the coexistence of species with lowand high nutrient requirements (Tilman 1982, 1987).

This model is not universally accepted, particularlybecause of emerging concern over the role of nutrientelevation in oligotrophic systems that lead to loss ofkelp forests that support diverse assemblages (Connell2007). These models predict recruitment failure ofcanopy-forming species, particularly through theexpansion of fast-growing macroalgae (Valiela et al.1997; Airoldi 2003). Stimulation of algal growth bynutrients is related to ecophysiological traits of algae,which are also related to algal morphology (Karez et al.2004).Thin and foliose algae with a high surface area tovolume ratio tend to have faster growth rates and highernutrient requirements relative to thicker algae with alower surface area to volume ratio (Pedersen & Borum1996). Foliose algae, therefore, may suffer from nutri-ent limitation in oligotrophic water and they mightbe disproportionately benefited by nutrient enhance-ments.Variations in nutrient supply also have direct andindirect effects on the abundance of invertebratespecies.

The effects of nutrient supply may depend on dis-turbance and vice versa (Huston 1994; Kondoh2001). Interactive effects of nutrients and disturbanceon diversity have been observed in both terrestrial(Proulx & Mazumder 1998) and aquatic ecosystems(Worm et al. 2002). For instance, strong effects ofnutrient enhancement on diversity and composition ofmarine benthic communities have been documented

*Corresponding author.†Deceased 24 August 2005Accepted for publication December 2007.

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in habitats exposed to low levels of disturbance, such asestuarine and wave-protected bays (e.g. Valiela et al.1997; Holmer et al. 2003; Elías et al. 2005). In thosesystems, relatively low water exchange may facilitatehigh local primary production (Pihl et al. 1999) andblooms of ephemeral algae due to nutrient additions(Raffaelli 1999). Contrarily, experiments conducted insystems where biotic and abiotic forces impose highlevels of mortality report limited effects of nutrientadditions (Bokn et al. 2003; Kraufvelin et al. 2006;Valdivia & Thiel 2006). Consumers that provide newspace (i.e. a disturbance) can control diversity (Nielsen& Navarrete 2004). For example, grazers may shiftthe relative dominance of habitats (Russell & Connell2005) by foraging differently in the presence of nutri-ents (Russell and Connell, 2007), These contrastingpatterns suggest that disturbance restricts the effects ofnutrient additions on diversity.Alternatively, if nutrientinput is positively related with the ability of organismsto withstand mortality and reoccupy disturbance-generated patches (Proulx & Mazumder 1998), theeffects of disturbance may depend on the availability oflimiting resources in the system.

In an oligotrophic system, we tested the indepen-dent and interactive effects of nutrient supply anddisturbance frequency on developing assemblages ofepibiota on vertical surfaces.We examined (i) whetherdisturbance, as periodical events of destruction, canmediate the effects of nutrients on diversity and com-position of assemblages of epibiota; (ii) whether theeffects of disturbance depend on nutrient supply; and(iii) whether heterogeneity of nutrient supply per seelevates diversity.

METHODS

Study site

A field experiment was conducted in Abalone Cove, inthe West Island Aquatic Reserve, South Australia(35°36′21″S, 138°35′31″E). The wave-exposed coastat West Island represents an oligotrophic system(Rochford 1979; Russell & Connell 2005). The seafloor at the study site is characterized by granite boul-ders (mean 300 mm across), supporting extensivestands of the kelp Ecklonia radiata as well as mixed-species aggregations with canopy-forming Cystophoraspp. and Sargassum spp. (Irving & Connell 2006).Theunderstorey in the region where the study site waslocated is dominated by encrusting coralline algae,while filamentous algae are abundant in gaps in thecanopy (Connell 2003). Foliose algae are abundantunder mixed-species canopies, as well as in open gaps(Connell 2003; Irving et al. 2004). Benthic consumershad no access to our experiment which was suspended

in the water column (see below), and no benthic con-sumer recruited onto the experimental units. Finally,pelagic consumers of benthic algae are scarce at thestudy site (S. D. Connell, pers. obs. 2003) and werenot observed in the experiment.

Experimental design

The effects of nutrients (three levels) and disturbancefrequency (seven levels) were tested in a modifiedsplit-plot experiment (Winer et al. 1991; Underwood1997), in which artificial substrata, made of PVCpanels, were used as experimental units. Artificial sub-strata, like pier pilings, pontoons and marine facilities,simulate major coastal habitats for marine organisms(Connell 2000). Even when the composition of assem-blages developing on contrived substrata differs fromthose developing on natural substrata (Connell 2000;Bulleri 2005), a substantial part of marine ecologicaltheory is based on early and recent studies conductedon these structures (e.g. Sutherland & Karlson 1977;Dean 1981; Kay & Keough 1981; Anderson 1999;Bullard et al. 2004; Clark & Johnston 2005).

Twelve grey polyvinyl chloride (PVC) rings(250 mm high, 600 mm diameter, 3 mm thick) wereindividually suspended at a depth of 0.5 m each onebelow a 20 L float and moored to the seafloor. Ringswere 4.5 m off the seafloor. Each ring was assigned toone of the three levels of nutrients. Moorings wererandomly positioned at >8 m spacing to assure theindependence between rings from different nutrienttreatments, as >5 m spacing guarantees that nutrientsdo not flow from enriched to control experimentalunits (Russell et al. 2005). Nine 150 ¥ 150 ¥ 3 mmPVC settlement plates (experimental units) were ver-tically attached with cables ties to the inner side ofevery ring at a distance of 5 cm between adjacentplates. The surface of each plate facing the centre ofthe ring was roughened with a 60-grit belt-sander to aconsistent texture. Seven disturbance treatments wereallocated randomly to panels in such a way that everytreatment appeared at least once within each ring, withone extra replicate of two of the treatments (i.e. 7disturbance treatments + 2 extra replicates = 9 platesper ring). These additional replicates were assigned sothat the experimental design yielded five replicates ofevery combination of nutrients ¥ disturbance.

Treatments

Nutrient concentrations in the water column aroundsettlement plates were increased by using a coated,slow-release fertilizer (Aglukon Plantacote Plus 6 M),which contains nitrogen (14%), phosphate (9%),potassium (15%) and small amounts of magnesium

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(2%) and micronutrients. Fertilizer beads were filledin nylon mesh bags and attached to rings in the 5 cmgaps between adjacent settlement plates. Nutrientlevels were ‘ambient’ (0 g fertilizer and 1000 g gravelfilling per ring = control), ‘medium’ (500 g fertilizerand 500 g gravel filling per ring) and ‘high’ (1000 gfertilizer and 0 g gravel filling per ring). As PlantacotePlus fertilizer was shown to enhance in situ nutrientconcentrations for at least 6 weeks (Worm et al. 2000),fertilizer was exchanged monthly to maintain a con-stant level of enrichment. Previous studies using 12 gof slow release fertilizer onto 60 ¥ 60 cm plots innatural reefs of West Island showed a significantincrease of nitrate concentrations by approximately80% above ambient levels (Gorgula & Connell 2004;Russell & Connell 2005; Russell et al. 2005). Due tothe relatively exposed position of our experiment in thewater column, we had to use a 15-fold larger amountof fertilizer than the previous studies to produce nutri-ent enhancement of comparable magnitude.

To determine the minimum effectiveness of the fer-tilizer to increase nutrient levels, water samples werecollected from each plot after fertilizer was used for 4weeks in the field. Subsamples of approximately5 mL water were taken at a distance of approximately5–10 cm from the central area of each plate within aring, using a 50 mL syringe. Samples were filtered inthe field through a 47-mm filter and filtrate wasfrozen (-20°C) prior to analysis for concentrations ofammonia and nitrate in the Australian Water QualityCentre. We focused on nitrogen-based compoundsbecause nitrogen availability is generally consideredto limit the growth of marine macroalgae (Fujita1985; Hodgkiss & Lu 2004). This survey allowed fordetection of increases in nutrient levels at the earlystage of the experimental period, but fluctuationsover time were undetectable. As a complement, wetested whether nutrient enhancement significantlyaffected algal production, by comparing algal per-centage cover of undisturbed assemblages amongnutrient levels.

A disturbance was defined as an event that changedthe niche opportunities available to the species of asystem (Shea et al. 2004). Where space for settlementis regarded as a limiting resource – for example inmarine benthic systems – any event that removesbiomass represents a disturbance (Grime 1977). Inthis study, a single disturbance event comprised theremoval of biomass from two non-overlapping circularareas (4.5 cm diameter), that is, 14% of total platearea. The disturbed areas were randomly positionedwithin a 25-field grid, which included the whole plate.Therefore, already disturbed areas could have beendisturbed during successive disturbance events. Plateswere disturbed 0, 2, 3, 4, 5, 7 and 12 times throughoutthe manipulation period (treatments 0¥ to 12¥) anddisturbance events were evenly distributed over time.

As disturbances were applied on discrete areas withineach experimental unit, the resulting assemblage oneach plate consisted of a mosaic of patches of differentsuccessional ages.This component of the design coun-teracted the potential confounding effect of distur-bance frequency and time since last disturbance.Disturbance manipulations were scheduled at 2-weekintervals.

For assessing the effectiveness of the disturbancetreatment in altering the diversity and abundance ofthe macro-benthic assemblages, percentage cover priorto and after each disturbance event was estimated forthe most frequently disturbed assemblages.

Sampling

The experiment was conducted between 16 August2003 and 10 April 2004. Colonization of plates wasnot manipulated during the first 12 weeks. On 10November 2003, prior to manipulations, the sessilemacrobenthic assemblage of all plates was non-destructively sampled to determine diversity andspecies composition. The last disturbance manipula-tion took place on 1 April 2004. Subsequent samplingsof all plates were conducted on 6 January, 29 Februaryand 10 April 2004; that is, every 8 weeks after manipu-lation started.

At each sampling date, rings were taken out of thewater and plates cut loose for examination in the fieldof the assemblages growing on the panels. Duringsampling, plates were constantly submerged and pro-tected from direct exposure to sun light. To reduceedge effects, estimations were restricted to the central13 ¥ 13 cm area of each plate. Estimations of percent-age cover to the nearest 5% of bare surface and eachmacrobenthic species (>1 mm), including epibionts,were made with a magnifying glass. Rare taxa (<5%)were assigned an arbitrary value of 1%. Percentagecovers of smaller organisms, like tube-dwelling amphi-pods and benthic diatoms, were also recorded butexcluded from final analyses to avoid comparisons oftaxa from different size spectra. As the assemblagespresented a multilayered structure, total percentagecover was allowed to exceed 100%. Organisms weredistinguished in the field to the lowest possible taxo-nomic grouping on the basis of readily visible mor-phological differences, and later identified underdissecting microscope to species level where pos-sible. Organisms identified up to genus and showingminimal morphological differences, that is, belongingto the same species, were grouped under the speciesepithet ‘sp.’ After the last sampling, dry weight (here-after biomass) of the assemblage of each plate wasdetermined after all species cover was removed anddried to constant weight at 60°C.

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Univariate analyses

Species richness (S, defined as the number of taxo-nomic identities) was recorded and evenness (J′) cal-culated from percentage cover data, using theformula J′ = -SS

i=1 Log(pi) pi Log(S)-1, where pi is thecover of species i divided by the total cover of Sspecies. These estimators of diversity were usedbecause they are intuitively related to ecological pro-cesses (Stirling & Wilsey 2001). For instance, lowJ′-values express numerical dominance by fewspecies, which might be related to competitive dis-placement. In any case, proportional diversity(Shannon–Wiener H′, data not shown) and J′ gavethe same patterns. Univariate analyses on data from34-week-old assemblages were separately conductedon S, J′ and on percentage cover (hereafter abun-dance) of algae and invertebrates. Calculation of Sand J′ included both algal and invertebrate speciesdue to the low contribution of the later. Analyseswere repeated after exclusion of invertebrates todeterminate the effect of lumping both groups. Priorto analyses, data were graphically explored to decideon appropriate transformations. When needed,dependent variables were arcsine, square-root orLog10 transformed. After data exploration, homoge-neity of variances was formally tested with Cochran’stest. Hypotheses about effects of nutrients, distur-bance and their interaction were tested using analysesof variance (anova). The linear mixed modelincluded disturbance and nutrients as fixed factorsand ring as a random factor, nested within nutrients.The residual term of the linear model was calculatedfrom the variability between the two replicated dis-turbance treatments within each ring, which allowedfor testing the significance of ring and ring ¥disturbance error terms (Underwood 1997). Errorterms that were highly insignificant (P � 0.25) wereeliminated from the model and the residual wasrecalculated in order to increase the power of hypoth-eses testing (Winer et al. 1991). Due to the lack ofcomplete replication within each ring, we used typeIII sums of squares for estimation of variances, whichis appropriate for unbalanced designs (Quinn &Keough 2002). Univariate analyses were carried outusing STATISTICA 7.1 software package.

We used orthogonal polynomial contrasts withineach nutrient level to test whether the functionalresponse of diversity to disturbance varied among thenutrient levels. Linear and quadratic models weretested in sequential regression analyses as part of theanova table. This method is proposed in the analysesof functional responses to assure the independencebetween the different regression models (Sokal &Rohlf 1995). If both linear and quadratic models weresignificantly adjusted, the quadratic fit was acceptedover the linear fit.

Multivariate analyses

Multivariate data were analysed with a distance-based permutational multivariate anova (permanova,Anderson 2001; McArdle & Anderson 2001).Hypotheses on the main and interactive effects ofnutrients and disturbance on assemblage composi-tion were tested using a mixed linear model, andeach term of the analysis was coded as a designmatrix using the XMATRIX.exe computer program(Anderson 2003) and tested individually with theappropriate error term using DISTILM.exe (Ander-son 2004b). Calculation of residuals and eliminationof highly insignificant error terms were conducted asin the univariate analyses. permanova was conductedon the basis of Bray–Curtis dissimilarities onuntransformed data, and each term of the model wastested using 4999 random permutations. Permutationof residuals under a reduced model was preferredinstead of the exact test, because the additionalrestrictions required for the exact test usually resultin tests with very low power (Anderson & Ter Braak2003). P-values were obtained using Monte Carlosamples from the asymptotic permutation distribu-tion because there were not enough permutable unitsto get a reasonable hypothesis test by permutation(Anderson & Robinson 2001). Canonical analyses ofprincipal coordinates (CAP, Anderson & Willis 2003)were conducted based on the Bray–Curtis dissimilar-ity matrices. In order to visualize patterns in the mul-tivariate data, the first two canonical axes werecomputed using CAP.exe (Anderson 2004a) andgraphed on ordination plots. As this constrainedmethod considers the correlation structure amongspecies, it can detect patterns in the multivariate datathat may be not detected by unconstrained ordina-tion methods like nMDS (Anderson & Willis 2003).Using the SIMPER routine, the contribution of eachtaxon to average dissimilarities between treatmentswas assessed, and the more important taxa wereidentified (Clarke & Warwick 2001). SIMPER analy-ses were performed with PRIMER 5.

RESULTS

Validation of treatment conditions

Concentrations of nutrients in the water columnsurrounding settlement plates increased monotoni-cally from ambient to high nutrient-enhancementtreatments. Ambient nutrient concentrations ofammonia and nitrate were 0.70 � 0.02 and 0.07 �0.01 mmol L-1, respectively (mean � SEM). Thesevalues are similar to values previously measured at

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the study site: for example, 0.72 � 0 and 0.064 �0.01 mmol L-1 for ammonia and nitrate, respectively(Russell & Connell 2005).Ammonia increased by 38%and 81% in medium and high nutrient treatments(0.99 � 0.05 and 1.29 � 0.31 mmol L-1), respectively,compared with ambient concentrations. Nitrate con-centrations were on average 16% and 38% higher inmedium and high nutrient treatments (0.08 � 0.01and 0.10 � 0.01 mmol L-1), respectively, than ambientnitrate levels. These differences, however, were notstatistically significant (anova, F2, 9 = 2.62 and 1.68for ammonia and nitrogen, respectively, P > 0.12).Nevertheless, the effects of nutrients were evidentin the biological data as indicated by significantincreases of algal abundances in nutrient-added plots(anova, F2, 12 = 5.93, P = 0.016), and experimentalmanipulation of nutrients is the only logical explana-tion of this. Abundances of algae were 44 � 5.91%,106 � 27.24% and 108.40 � 15.45% in ambient,medium and high nutrient treatments, respectively. Posthoc tests (SNK stepwise test) showed significant differ-ences between ambient and each enriched treatment.However, algal cover remained unchanged betweenmedium and high enrichment levels. The biomass ofthe epibiotic assemblages measured at the end of theexperiment was significantly and linearly related to totalpercentage cover: biomass (g) = -0.341 + 0.05 totalcover (%), P < 0.001, r2 = 0.767. Finally, total abun-dance was significantly reduced by a mean 14.8% at thetime of applying a single disturbance (t-test on paireddata: t131 = 5.98, P < 0.001).

10.2

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Encrusting coralline algaeMychodea sp.Ulva sp. Bare surface

b

Fig. 1. Temporal pattern (mean � SEM, n = 5) of speciesrichness S (a), and bare surface and the most abundant taxa(b) observed on control plates after the start of manipula-tions on November 2003.

Table 1. Summary of three-way nested anovas conducted using polynomial contrasts on species richness (S), evenness (J′)and on abundance of algae (A) and invertebrates (I )

Source of variation d.f.

Log10(S ) (J′)1/2 Log10(A) Arcsine(I)

MSdenF P F P F P F P

Nutrients, N 2 5.9 0.023 1.87 0.209 8.42 0.009 0.29 0.761 R(N)Disturbance, D 6 2.6 0.024 0.35 0.908 2.53 0.028 2.22 0.030 Pooled

Dlinear 1 2.3 0.130 0.28 0.597 2.26 0.137 7.93 0.006 PooledDquadratic 1 0.2 0.689 0.44 0.510 0.24 0.626 0.24 0.625 Pooled

N ¥ D 12 0.7 0.778 2.67 0.005 2.60 0.006 1.08 0.393 PooledN ¥ Dlinear 2 2.7 0.073 0.29 0.753 3.77 0.027 8.34 0.001 PooledN ¥ Dquadratic 2 0.3 0.711 2.91 0.061 4.93 0.010 0.51 0.600 Pooled

Ring(N ), R(N) 9 2.6 0.011 2.83 0.006 2.61 0.011 5.10 0.002 PooledD ¥ R(N) 54 0.9 0.678 0.95 0.580 0.89 0.646 0.95 0.581 ResidualResidual 21Pooled 75

The residual was calculated from the difference between the experimental units of the replicated disturbance levels withinrings. Elimination of error term D ¥ R(N), and recalculation of residual was done after verifying that s2

D¥R(N) = 0 with (notsignificant at a = 0.250). The term used as denominator mean square of each source of variation is given in the column MSden.Significant P-values at a = 0.05 are given in bold. Pooled term = D ¥ R(N) + Residual.

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Overview and univariate analyses

At the end of the experiment, 30 taxa were identified onthe plates.The most abundant and frequent taxa wereencrusting coralline algae, the green alga Ulva sp., andthe red alga Mychodea sp.Algae dominated the plates atan abundance of 75.86 � 3.38%, while invertebratescovered the plates on average by 3.82 � 0.29%.

Species richness (S) of control assemblages remainedconstant over time (Fig. 1a), while the abundance of

encrusting coralline algae peaked after 28 weeks andfurther decreased on week 34 (Fig. 1b). Ulva sp. andMychodea sp. developed at low abundances during suc-cession of the control plates, being below 10% in everysampling event (Fig. 1b). Finally, there was less than5% of bare surface after 28 weeks of succession(Fig. 1b), suggesting that primary substratum forsettlement became a limiting resource.

At the end of the experiment, S was significantlyaffected by nutrient treatments (Table 1). There were

S

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Fig. 2. Mean response of (a) species richness S and (b) evenness J′ of epibiotic assemblages to nutrients (ambient, mediumand high) and disturbance frequency (number of disturbance events over 22 weeks). Linear and quadratic regression modelswere sequentially tested on mean values of the dependent variables. Significant regression lines are shown. Values are given asmean � SEM. Note: Regression results for the significant fit of disturbance (D) on J′ at ambient nutrient level (J�a) are as follows.Sqrt(J′a) = 0.9107 - 0.0157D + 0.0012D2, F = 6.78, P < 0.05.

Table 2. Summary of permanova based on Bray–Curtis dissimilarities (without transformation) of the multivariate data

Source of variation d.f. MS Pseudo-F P-value MSden

Nutrient, N 2 5972.12 2.55 0.036 R(N)Disturbance, D 6 1414.46 1.93 0.014 PooledN ¥ D 12 1225.49 1.67 0.011 PooledRing(N ), R(N) 9 2335.25 3.19 <0.001 PooledD ¥ R(N) 54 757.47 1.00 0.524 ResidualResidual 21 755.73Pooled 75 731.30

P-values were obtained using 4999 Monte Carlo samples from the asymptotic distribution. Calculation of residual andelimination of insignificant error terms as in Table 1. The term used as denominator mean square of each source of variation isgiven in the column MSden. Significant P-values at a = 0.05 are given in bold. Pooled term = D ¥ R(N) + Residual.

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on average 1.7 and 2.3 more species in assemblagesexposed to medium and high treatments respectively,than at ambient nutrient levels (Fig. 2a, SNK post hocstepwise test). Forty-three per cent of all species werefound only at nutrient enriched assemblages, but atvery low abundances (on average 0.09 � 0.02% perspecies). The bryozoan Membranipora membranacearecruited only in moderately enriched assemblages.Seven species were only found at medium and highnutrient levels, including the red algae Champia zos-tericola and unidentified geniculate Corallinaceae sp.b, the green algae Chaetomorpha coliformis and Cla-dophora sp., the brown algae Padina sp. and Cystophorasp. and the bryozoan Celleporaria sp. Five species werepresent on highly enriched plates only: an unidentifiedred alga, the green alga Caulerpa trifaria, the brownalga Sargassum sp., the ascidia Botryllus schlosseri andthe bivalve Venerupis anomala. On the other hand, dis-turbance treatments resulted in a significant reductionof S (Fig. 2a, Table 1). However, neither the testedregression models (Table 2) nor the SNK post hoc testshowed a significant pattern. The less conservativeLSD post hoc test and inspection of means revealed

that S was significantly higher at treatments 0¥, 2¥and 4¥ than at treatment 12¥. Finally, no interactiveeffect of nutrients and disturbance on S was detected(Table 1).

After removing the faunal species from the calcula-tion of S, the effect of nutrients remained statisticallysignificant (anova, F2, 9 = 5.64, P = 0.025), but theeffects of disturbance disappeared (anova, F6, 75 =0.99, P = 0.435). The interaction term was still insig-nificant after removing faunal species from S (anova,F12, 75 = 1.16, P = 0.324).

Evenness (J′) tended to decrease with nutrientand disturbance treatments (Fig. 2b). However, theincrease of J′ at 12¥ in the ambient nutrient regimeresulted in a significant nutrient ¥ disturbance inter-action (Fig. 2b, Table 1). This pattern did not changeafter removing invertebrates from the calculation of J′(anova, F12, 75 = 2.92, P = 0.002).

Nutrients and disturbance interactively affected algalabundance, as the shape of the disturbance-abundancecurve of algae depended on the nutrient treatment(Fig. 3a, Table 1). At ambient nutrient levels, distur-bance resulted in a hump-shaped response of algal

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Fig. 3. Effects of nutrients (ambient, medium and high) and disturbance frequency (number of disturbance events over 22weeks) on the mean abundance (percentage cover) of (a) algae and (b) invertebrates. Linear and quadratic regression modelswere sequentially tested on mean values of the dependent variables. Significant regression lines are shown. Values are given asmean � SEM. Note different scaling of the ordinates. Note: Regression results for each significant relationship (P < 0.05) are asfollows. Algae at ambient nutrient level (Aa): Log10(Aa) = 1.436 + 0.022D - 0.002D2, F = 8.38; Algae at high: Log10(Ah) =1.626 - 0.010D, F = 4.57; Invertebrates at ambient (Ia): Arcsine(Ia) = 42.212 - 2.356D, F = 7.40; Invertebrates at medium (Im):Arcsine(Im) = 48.675 - 2.617D, F = 11.15; Invertebrates at high: (Ih): Arcsine(Ih) = 45.136 - 1.654D, F = 4.61.

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abundance (Fig. 3a). At medium nutrient level, distur-bance frequencies of 0¥ and 2¥ presented a higher algalabundance relative the other disturbance frequencies(Fig. 3a), but neither the linear nor quadratic curve wassignificantly fitted (Table 1). SNK stepwise compari-sons revealed two statistically different groups withinthe medium nutrient level: 0¥ = 2¥ > 3¥ = 4¥ = 5¥ =7¥ = 12¥. Finally, at highly enriched conditions distur-bance resulted in a significant and monotonic decreaseof algal abundance (Fig. 3a).

Disturbance treatments significantly reducedinvertebrate abundance (Fig. 3b, Table 1). Inverte-brate abundance decrease was strongest at mediumnutrient level and least at high nutrient treatments(Fig. 3b). Finally invertebrate abundance was neitheraffected by nutrients nor by the interaction of nutrientand disturbance treatments (Fig. 3b, Table 1).

Multivariate analyses

The significant nutrient ¥ disturbance interactiondetected by the multivariate analyses (Table 2) indi-cated that the differences between disturbance treat-ments were dependent on nutrient levels. Accordingly,we performed separate multivariate analyses on theeffects of disturbance at each nutrient level. Separatepermanova showed that the effects of disturbancewere significant at ambient and medium nutrientregimes, but these effects were not apparent at highlyenriched assemblages (Table 3). Within non-enrichedassemblages, the highest dissimilarities were foundbetween assemblages from 0¥ and 5¥ disturbance fre-quencies, and between disturbance frequencies of 3¥and 12¥ (Fig. 4a). Within medium nutrient level, thehighest dissimilarities were detected between 2¥ and12¥, and between 2¥ and 7¥ disturbance treatments(Fig. 4b). According to SIMPER routines, six specieswere important in differentiating assemblages fromdifferent disturbance levels at each nutrient level

Table 3. Summary of separate permanova testing the effects of disturbance in each level of nutrients based on Bray–Curtisdissimilarities of the multivariate data

Source of variation d.f.

Ambient Medium High

MSdenMS F P MS F P MS F P

Disturbance, D 6 1254.70 2.2 0.004† 1727.20 2.0 0.019 883.57 1.0 0.430 PooledRing, R 3 2016.50 4.7 <0.001 1695.70 2.0 0.058 3212.3 3.7 0.002 PooledD ¥ R 18 562.76 1.3 0.206 782.27 0.9 0.710 833.50 0.9 0.656 ResidualResidual 7 430.54 923.95 940.23Pooled 25 No pooling 852.17 862.95

P-values were obtained using 4999 Monte Carlo samples from the asymptotic distribution. Calculation of residual andelimination of insignificant error terms as in Table 1. The term used as denominator mean square of each source of variation isgiven in the column MSden. Significant P-values with alpha = 0.05 are given in bold. Pooled term = D ¥ R + Residual. †D ¥ R wasused as error term.

Medium

-0 2

0.0

0.2

-0.3 0.1 0.1 0.3

Can

onic

alA

xis

2

b

Canonical Axis 1

0.3

Ambient

Can

onic

al A

xis

2 0.1

0.4-0.4 -0.2 0.0 0.2-0.3

-0.1

a

Canonical Axis 1

0x

2x

3x

4x

5x

7x

12x0.3-0.1 0.1

-0.3

-0.1

0.1High

c

Can

onic

al A

xis

2

Canonical Axis 1

Fig. 4. Canonical ordination plot for the interactive effectsof nutrients (ambient, medium and high) and disturbancefrequency (number of disturbance events over 22 weeks) onthe composition of 34-week-old epibiotic assemblages.

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(Table 4). The contribution from Ulva sp. to the dis-similarities increased with the nutrient treatment(Table 4).The abundance of Ulva sp. was between 0%and 10% at the ambient nutrient level, increasing atlow disturbance frequencies of the medium nutrienttreatment, and decreasing with disturbance at the highnutrient level (Fig. 5). Encrusting coralline algae fol-lowed a similar pattern to Ulva sp., but the formerpresented higher abundances at the ambient nutrientlevel than the latter (Fig. 5). On the other hand, it wasnot possible to determine a logical pattern in the abun-dance of Mychodea sp. (Fig. 5).

DISCUSSION

Nutrient and disturbance regimes had opposingeffects on the development of species richness ofepibiota. The small nutrient increase caused species

richness to increase, while disturbance caused speciesrichness to decrease. The identity of the constituentspecies (i.e. species composition), however, wasaffected by an interaction between nutrient and dis-turbance regimes. The abundance of the thin foliosealga (Ulva sp.) increased with nutrients and at thesame time this increase was mediated by disturbance.The abundance of invertebrates, however, was consis-tently sparser among all disturbance treatments inde-pendent of nutrient concentration.

Our findings, together with previous results lendsupport to the Resources Heterogeneity Hypothesis(Tilman 1982, 1987). In our oligotrophic system, thishypothesis correctly predicts that nutrient enhance-ment causes an increase of diversity of epibiotagrowing on vertical substratum. Nutrient addition inoligotrophic systems may increase temporal or spatialvariability of resources, allowing diversity to increaseby adding resource-rich microhabitats that support

Table 4. Breakdown of Bray–Curtis dissimilarities between communities from different disturbance frequencies (0¥ to 12¥)into contributions from the most important taxa (δi %)

Taxa

Nutrients

Ambient Medium High

δi % δ δi iSD( ) δi % δ δi iSD( ) δi % δ δi iSD( )

Ulva sp. 10.31 0.777 31.150 1.287 30.0 1.210Encrusting coralline algae 22.47 1.726 18.930 1.514 18.4 1.340Mychodea sp. 18.22 1.172 11.710 1.330 13.8 1.250Unidentified brown algae 12.01 1.077 6.019 1.060 3.1 0.880Galeolaria sp. 6.54 1.097 3.275 1.153 3.0 1.114Cladosiphon filum 7.67 5.825 2.858 0.970 3.6 0.991

Values are averaged over all pairwise treatment comparisons between disturbance frequencies and within each nutrient level(ambient, medium, high). A high value (�1) of the ratio δ δi iSD( ) indicates that the taxon consistently contributes toδi % across all pairs of samples in the two groups being compared.

Abu

ndan

ce [%

-cov

er]

0

20

40

60

80

Ulva sp.Encrusting coralline algaeMychodea sp.

0 3 6 9 12 0 3 6 9 12 0 3 6 9 12

Disturbance frequency

Ambient Medium High

Abu

ndan

ce [%

-cov

er]

0

20

40

60

80

Ulva sp.Encrusting coralline algaeMychodea sp.

0 3 6 9 12 0 3 6 9 12 0 3 6 9 12

Disturbance frequency

Ambient Medium High

Fig. 5. Effects of nutrients (ambient, medium and high) and disturbance frequency (number of disturbance events over 22weeks) on the abundance of the most important taxa explaining the dissimilarities between groups at the end of the experiment.Values are given as mean � SEM.

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species with higher nutrient requirements (Tilman1987).

Despite natural concentrations of nutrients andrelative increases being substantially less than moststudies that manipulate nutrient inputs to macro-benthic communities (reviewed by Worm et al. 2000),this small increase in nutrient supply had detectableeffects on the assemblage. It is possible that macro-benthic assemblages from oligotrophic waters may bedisproportionately more sensitive to nutrient enhance-ment (Russell et al. 2005).This would have ecologicalconsequences for benthic assemblages that are in closeproximity to watersheds that discharge elevated con-centrations of nutrients, contingent on their regionalcontext (Connell 2007).

Disturbance had a negative effect on species rich-ness and invertebrate abundance independently ofnutrient concentration. Additionally, there was noeffect of nutrients on invertebrates, even though larvalsettlement can be stimulated by organic enrichment(Morse et al. 1979; Pechenik & Heyman 1987). Incomparison with algae, the relatively slower growinginvertebrates might have had insufficient recruitmentand growth rates to regain lost cover at higher frequen-cies of disturbance; resulting in the apparent loss offaunal species.

Nutrients and disturbance interactively affectedassemblage composition, given the disproportionallylarge disturbance-induced effects at medium nutrientconcentrations. Foliose algae can have high growthrates, nutrient requirements and nutrient uptake (Ped-ersen & Borum 1996), and may be nutrient limitedunder nutrient-poor conditions. These ecophysiologi-cal traits might explain the increase in percentage coverof Ulva sp. under nutrient enhancement. The unex-pected unimodal response of algal abundance to distur-bance at ambient nutrient levels may be related to anincrease in available space for settlement at intermedi-ate disturbance frequencies, which was occupied by fewsuperior coloniszers. This may explain the U-shapedresponse of evenness to disturbance at ambient nutrientlevel, albeit this interpretation relies on a single pointthrough which this regression was shaped.

In conclusion, nutrient and disturbance regimes hadopposing effects on diversity such that species richnessincreased with resource enhancement (nutrients) anddeclined with disturbance (provision of new space).These results lend some support to the model thatincreased heterogeneity of distribution of limitingresources allows the coexistence of species with lowand high resource requirement (Tilman 1982).

ACKNOWLEDGEMENTS

Financial support for the study was provided byFoundation Mercator GmbH to MW an ARC grant to

S. D. C. Stuart Jenkins, Michael Huston, and twoanonymous referees gave constructive criticism on themanuscript. For donation of fertilizer we thankAglukon GmbH, Düsseldorf, Germany.This contribu-tion is dedicated to the memory of our friend Jarrod D.Stehbens (1982–2005) and his love of southern seas.

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