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Sea urchin control of macroalgal communities across a productivity gradient

Article in Journal of Experimental Marine Biology and Ecology · December 2019

DOI: 10.1016/j.jembe.2019.151248

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Contents lists available at ScienceDirect

Journal of Experimental Marine Biology and Ecology

journal homepage: www.elsevier.com/locate/jembe

Sea urchin control of macroalgal communities across a productivity gradientN. Kriegisch, S.E. Reeves, C.R. Johnson, S.D. Ling⁎

Institute for Marine and Antarctic Studies, University of Tasmania, 20 Castray Esplanade, Battery Point, Tasmania 7004, Australia

A R T I C L E I N F O

Keywords:UrbanisationEutrophicationHerbivoryGrazingHerbivore exclusionOctocoralSeaweedUrchin barrensPhase-shift

A B S T R A C T

Opposing bottom-up ‘resource-driven’ and top-down ‘consumer-driven’ forces interact to shape the structure ofecosystems. While these counteracting forces are well recognised, debate remains regarding which is more in-fluential across space and time. Here we explore bottom-up versus top-down control of macroalgal communitiesfor temperate rocky reef communities in highly urbanised Port Phillip Bay (PPB), southeast Australia. Fieldsurveys show macroalgal cover to paradoxically decline with increasing ‘bottom-up’ nutrient inputs while theabundance of grazing sea urchins (Heliocidaris erythrogramma) increased. The mechanisms underpinning thispattern were examined by constructing urchin-exclusion plots using octocoral (Erythropodium hicksoni) coloniesthat grow on urchin barren grounds and form natural barriers to grazing sea urchins. Octocoral plots wereconstructed by cutting 200 mm by 200 mm squares to expose bare reef substratum within the centre of octocoralcolonies, which enabled efficient replication of urchin-exclusions on barren grounds across three distinct zonesof anthropogenic nutrient input in PPB. Octocoral plots successfully excluded urchins across zones and, in theabsence of grazing, macroalgal production increased with increasing nutrient concentration as expected. Thisnovel opportunity to efficiently replicate urchin-exclusions on high-density barren grounds across different zonesof ‘bottom-up’ forcing demonstrates that urchin overgrazing can keep pace with and overwhelm increasingmacroalgal productivity. Our findings also highlight that impacts of grazing can be greatest where bottom-upforces enable large abundances of herbivores to accumulate, which is counter to perceptions that impacts ofherbivores will be greatest where macroalgal productivity is low.

1. Introduction

The structure and function of ecosystems is determined by an arrayof factors, which can be classified into ‘bottom-up’ (resource driven)and ‘top-down’ (consumer driven) forces (Hairston et al., 1960). Spa-tiotemporal variability in the relative importance of these ‘drivers’ andthe complex interactions between them are well recognised (Hunterand Price, 1992; Power, 1992; Terradas and Penuelas, 2011;Tamburello et al., 2019). The availability of resources for primaryproducers, such as nutrients, and the ‘flow-up’ effects to secondaryconsumers at higher trophic levels defines bottom-up control. Top-down effects generally refer to consumers impacting the abundance of‘prey’ species, which can ultimately control primary producers. Thus,both the productivity and biomass density of primary producers dependon resource availability and the magnitude of grazing pressure (e.g.Worm and Lotze, 2006, Burkepile and Hay, 2006). This generality holdstrue for shallow subtidal reefs able to support benthic macroalgae(Hauxwell et al., 1998; Atalah and Crowe, 2010; Guarnieri et al., 2014).

Increasingly, human influences are altering the magnitude and ef-fects of both bottom-up and top-down forces on marine ecosystems

(Hiddink and ter Hofstede, 2008; Noriega et al., 2012; Muthukrishnanand Fong, 2014). For example, herbivore abundance can be alteredthrough fishing either directly by removing grazers, or indirectly byremoving predators of grazers (i.e. ecological overfishing), which canlead to population explosions of herbivores (Hobday et al., 2000;Tegner and Dayton, 2000; Smith et al., 2001; Jenkins, 2004; Shears andBabcock 2002; Ling et al., 2009). In terms of bottom-up effects, nu-trification of coastal areas due to nutrient inputs from growing humanpopulations is a concern, and may include nutrient enrichment fromsewage, plus other urban and agricultural run-off, which usually in-creases the productivity of macroalgae (Russell et al., 2005; Elsdon andLimburg, 2008; Gorman et al., 2009). It is therefore important to un-derstand how human influences alter the balance between primaryproduction and grazing of coastal macroalgae so that managementpractices can be informed, and future environmental trends may beidentified.

The production (gross or net) of macroalgae can only be assessedwhen significant grazers are successfully excluded, which can be lo-gistically challenging in subtidal marine environments. Excluding gra-zers often requires either building cages (Martinetto et al., 2011) or

https://doi.org/10.1016/j.jembe.2019.151248Received 31 May 2019; Received in revised form 4 October 2019; Accepted 9 October 2019

⁎ Corresponding author.E-mail address: [email protected] (S.D. Ling).

Journal of Experimental Marine Biology and Ecology xxx (xxxx) xxxx

0022-0981/ © 2019 Published by Elsevier B.V.

Please cite this article as: N. Kriegisch, et al., Journal of Experimental Marine Biology and Ecology, https://doi.org/10.1016/j.jembe.2019.151248

http://www.sciencedirect.com/science/journal/00220981https://www.elsevier.com/locate/jembehttps://doi.org/10.1016/j.jembe.2019.151248https://doi.org/10.1016/j.jembe.2019.151248mailto:[email protected]://doi.org/10.1016/j.jembe.2019.151248

artificial reefs (Russell and Connell, 2005; Kriegisch et al., 2016), hencethese experiments are usually difficult to establish and maintain, andtypically require extensive procedural controls to account for experi-mental artefacts. For this reason these kinds of experiments are oftenlimited to only a single location making findings less informative acrossspace (e.g. Hillebrand, 2003; Vanderklift and Kendrick, 2005; Smithet al., 2010).

Here we examine the relative strengths of top-down and bottom-upcontrol for subtidal reefs spanning strong gradients in grazer densityand nutrient inputs within Australia's largest and highly urbanisedembayment, Port Phillip Bay, Victoria. We conduct field surveysshowing macroalgae to counterintuitively decline yet grazing seaurchins (Heliocidaris erythrogramma) to increase with increasing‘bottom-up’ forcing across distinct zones of nutrient input in PPB. Todetermine the effect of different nutrient input regimes on macroalgaein the absence of grazing urchins, we use the naturally occurring urchinbarrier, the octocoral Erythropodium hicksoni (Ling et al., 2019a) toexclude urchins from rocky reefs. Specifically, we test the hypothesisthat top-down urchin grazing overwhelms the bottom-up forcing onalgal productivity in this rocky reef system.

2. Materials and methods

2.1. Study system

Port Phillip Bay (PPB) in Victoria is Australia's largest embayment(Harris et al., 1996) (Fig. 1). Here, reef surveys and the urchin-exclu-sion manipulative experiment were conducted on the shallow rockyreefs (approx. 3.5–4.5 m depth) spanning three distinct anthropogenicnutrient input zones (Currie and Parry, 1999; Fulton and Smith, 2002;Johnson et al., 2015; Lee et al., 2015; Ling et al., 2018) (Fig. 1). TheWestern Zone of PPB is close to a large sewage treatment plant (WesternTreatment Plant), which services the majority of Melbourne's popula-tion (~4.5 M people) and causes high anthropogenic nutrient inputsinto the Bay (up to 3600 t nitrogen and 930 t phosphorus annually;Harris et al., 1996). The Northern Zone is proximate to the mouth of amajor water course (Yarra River) that flows through the metropolitanarea of Melbourne, which supplies up to 1700 t nitrogen and 450 tphosphorus annually into the Bay (Harris et al., 1996). Whereas theSoutheast Zone is in closer proximity to the entrance of PPB and isrelatively pristine compared to the other zones in terms of receivingreduced urban nutrient inputs (e.g. Harris et al., 1996; Lee et al., 2015;Ling et al., 2018).

2.2. Surveys of macroalgal cover and sea urchin abundance across zones

Broadscale patterns in macroalgal community composition and seaurchin abundance and biomass were surveyed across the different nu-trient input zones of PPB. Percentage cover of macroalgae was visuallyassessed in situ by divers within five 0.25 m2 point-intercept quadrats

(surveying an area of 1.25 m2) that were laid at 10 m intervals along a50 m transect line placed at each of 6 reefs within each of the nutrientinput zones during Spring (October/ November), see (Fig. 1). Macro-algal taxa present at each of 50 intersecting points (defined by theperpendicular intersection of strung wires within the quadrat) werethen multiplied by two to obtain percentage cover estimates for eachmacroalgal taxa (resolved to species-level where possible, or genus-level). The total number of intersecting points counted could exceed 50points (i.e. > 100% cover) as algal taxa composing the overstory, un-derstory and substratum were assessed.

The abundance of grazing sea urchins (Heliocidaris erythrogramma)was scored concurrently by counting the total number of individualswithin each quadrat. Because urchin size varied widely between reefs(see Ling et al., 2019b), the biomass density of sea urchins was calcu-lated by allometric conversion based on the zone-specific relationshipbetween length and wet weight obtained by measuring the test dia-meter of N= 10 randomly collected urchins from each of 6 reefs withineach zone (see Fig. 1; i.e. high nutrient input (West) zone, biomass(g) = 0.0007 × 2.85, R2 = 0.97; intermediate nutrient input (North)zone, biomass (g) = 0.0013 × 2.69, R2 = 0.96; low nutrient input(Southeast) zone, biomass (g) = 0.0009 × 2.79, R2 = 0.98). Note thatbecause of the non-linear relationship, the allometric equation was usedon each urchin individually to estimate individual biomass, and thenthe average of these biomasses at each site was subsequently averagedat the level of zone and multiplied by the density of individuals toobtain biomass density (g m−2) estimates.

Survey data for macroalgal percent cover (canopy-forming speciesand all erect macroalgae) plus sea urchin abundance data (density andbiomass) were compared across the three nutrient input zones of PortPhilip Bay using 1-way ANOVA with 6 replicate reef transects per zone(see Fig. 1). All univariate analyses were performed in R (The RFoundation for Statistical Computing, Version 3.3.1, © 2016). Wherenecessary, transformations to stabilise variances were determined bythe Box-Cox procedure in R (available in the MASS package). All mul-tivariate community analyse were conducted using the PRIMER soft-ware (Version 6.1.12 and PERMANOVA+ Version 1.02, © 2009PRIMER-E Ltd.), with patterns in macroalgal communities across nu-trient input zones analysed using 1-way Permutational MultivariateAnalysis of Variance (PERMANOVA) conducted on Bray Curtis simi-larity matrices (generated from square root transformed data).

2.3. Urchin-exclusion experiment across zones

A naturally occurring biological barrier to grazing sea urchins, the oc-tocoral Erythropodium hicksoni (Ling and Kriegisch, submitted manuscript),was used to efficiently replicate urchin exclusions across nutrient inputzones of PPB. The encrusting colonial octocoral Erythropodium hicksoniprovides a barrier to the sea urchin Heliocidaris erythrogramma even onextensive urchin barrens (Ling et al., 2019a, this issue). From towed-diverobservations spanning a total distance of 27 km across each zone of PPB,

Fig. 1. Port Phillip Bay (PPB) Victoria, south-easternAustralia; large filled-symbols in the expanded view mark theurchin-exclusion experimental reefs and open-symbols showan additional five reefs surveyed within three of the fourdistinct nutrient input zones of The Bay (after Johnson et al.,2015), i.e. West (W = high nutrient input); North (N = in-termediate nutrient input); and Southeast (SE = low nutrientinput). Note that colonies of the octocoral Erythropodiumhicksoni were found to occur infrequently and not of suffi-ciently large size (~0.25 m2) to enable urchin-exclusion plotsto be established in the Southwest Zone.

N. Kriegisch, et al. Journal of Experimental Marine Biology and Ecology xxx (xxxx) xxxx

2

reefs with a high local abundance of large octocoral colonies (large enoughto completely cover boulders of approx. > 0.6 m diameter), were con-centrated on particular barrens reefs within each zone: i.e. Long Reef (S37°52′10.5564″, E 144°53′36.4884″) in the high nutrient input (West) zone;Williamstown (S 38°1′35.742″, E144034’58.5516″) in the intermediate nu-trient input (North) zone, and Schnapper Point (SE S 38°12′47.8836″, E145°1′56.5170″) in the low nutrient input (Southeast) zone (Fig. 1). Octo-coral colonies in the high nutrient input (West) zone were located on bar-rens reef at a depth of ~2.5 m composed of mixed rocky slabs and bouldersinterspersed with sand patches (101–102 m2). For the intermediate nutrientinput (North) zone, octocorals were located on barrens reef at a depth of~3.5 m depth composed of small boulders (< 1 m diam.) and cobble in-terspersed by small (101 m2) patches of sand. In the low nutrient input(Southeast) zone, octocorals were located on barrens reef at a depth of~4.5 m depth composed chiefly of medium boulders (< 2 m diam.) inter-spersed with flat rock and small patches of gravel and sand. The study reefswere of similar wave exposure (as estimated from fetch, Hill et al., 2010)and salinity, with both these additional environmental variables explaininglittle variability in macroalgal communities across Port Phillip Bay (Johnsonet al., 2015).

Grazer exclusions were focussed on sea urchins as they representedthe most active grazer with the highest biomass density and have aclear impact on reefs across Port Phillip Bay (Kriegisch et al., 2016,Kriegisch et al., 2019a, b; Reeves et al., 2018; Carnell and Keough,2019; Ling et al., 2019b). Herbivorous fish (e.g. Parma victoriae andGirella zebra) were not considered in this experiment because they oc-curred rarely on the study reefs and herbivory assays revealed negli-gible effects of their grazing on local macroalgae. That is, we assessedpotential grazing by herbivorous fish, by offering freshly cut algalpieces (Ecklonia radiata, 50 mm by 20 mm lateral fronds, n= 48 in totalin 4 zones of PPB) suspended by fishing line and a small float, so thatthey hovered within the algae canopy. Assays were conducted in allzones of PPB and revealed no grazing of algal pieces suspended abovethe reef over a 3-day period (see also Kriegisch et al., 2019b). Givenundetectable grazing by herbivorous fishes and successful exclusions ofbenthic invertebrate herbivores, the octocoral urchin-exclusion plotsacted as effective herbivore-exclusion treatment within this system.

Commencing in February 2012, eight large colonies of E. hicksoniencrusting flat tops of large boulders were selected on each urchin-exclusion reef (Fig. 1). ‘Octocoral plots’ (200 mm by 200 mm) were cutfrom the centre of colonies, ensuring that the removal areas were sur-rounded by an average of ~100 mm of octocoral on all sides (as in Linget al., 2019a). All underlying organisms were scraped clean from therock surface contained within the octocoral plot. The only requiredmaintenance of the octocoral plots was periodic trimming of the in-ternal octocoral edges every 2 to 3 weeks to ensure that the colony didnot grow back into the cleared plot area (average regrowth rate of0.23 mm day−1; Ling et al., 2019a).

After the establishment of each octocoral plot, a 200 mm by 200 mmbackground ‘control’ patch was randomly chosen on a nearby boulderwith no octocorals, which was marked by a stainless-steel pin secured tothe benthos with Z-Spar epoxy. The background ‘control’ patch was leftuntouched so that any recovery of algae within the urchin-exclusiontreatment over the duration of the experiment could be assessed re-lative to the algal community occurring in the presence of grazingurchins. The octocoral grows to a height of < 20 mm and has no ap-parent artefacts unlike artificial fences/cages (Ling et al., 2019a). Thefactors of “Treatment” (2 levels; urchin-exclusion and background‘control’) and nutrient input “Zone” (3 levels in PPB; West (high nu-trient input), North (intermediate nutrient input) and Southeast (lownutrient input)) were examined, with n= 8 replicates of each treatmentin each of the three zones (giving 16 plots per experimental zone and 48plots in total for the experiment).

2.3.1. Assessment of macroalgal responseAssessments of macroalgal development were conducted in urchin-

exclusion and background control plots after 2, 3 and 6 months of ex-clusion. Urchin abundance was also concurrently scored by countingthe total number of individuals within treatment and control plots.Biomass density of grazing sea urchins was calculated by allometricconversion based on the mean size of local urchins (n= 10 randomlycollected urchins) and converted to biomass using the zone-specificrelationship between length and wet weight (see above). The urchin-exclusion experiment was terminated after 6 months because someoctocoral colonies were beginning to break down along at least oneedge allowing ingress of urchins and access to macroalgae previouslyprotected within the octocoral-fence. Planar percentage cover of allmacroalgal species within each plot, plus abundances of sea urchins,were determined in situ on SCUBA by using a 200 mm by 200 mmquadrat, which was placed around the plot enabling planar percentcover to be visually determined by summing component species tonearest 5% increment, i.e. a 5% increment was approx. 50 mm2. That is,the cover of each and every algal taxon was systematically and cate-gorically scored for percent cover by summing its cover in 5% incre-ments. Where a particular taxon was present, but did not constitute theminimum 5% threshold, the taxon was scored as < 5% and nominallyassigned a cover of 1% to indicate presence. Each taxon was thus as-signed to a categorical percent cover within each experimental plot inthe categories of 0%, 1%, and increasing 5% increments. The cover ofall structural layers of macroalgae (canopy and foliose understory, butnot encrusting algae) was estimated, therefore total % algal coverwithin a plot could exceed 100%.

Mean algal production recovery rate was established for each zone bydetermining the increase in percentage cover of algae on the bare reefsurface contained within each urchin-exclusion plot. An index of algalproduction was also estimated for each zone by non-destructive in situmeasurement of the height of the tallestUlva sp. thallus (using stainless steelruler) in urchin-exclusion plots after 3 months during which time the typi-cally ephemeral Ulva showed an initial bloom. Maximum Ulva height wasconverted to fresh weight based on a length-weight power function de-termined as: Ulva (wet grams) =0.0002*(height Ulva in mm)1.85;R2 = 0.92, n= 26. Mean Ulva production for each zone was then expressedas the grams of Ulva accumulated per week.

2.3.2. Nutrient, light and temperature conditions during the urchin-exclusion experiment

To characterise macroalgal growth conditions during urchin-exclu-sions, nutrient concentration, light intensity and temperature were re-corded at each experimental reef. Nutrient concentrations were de-termined from three replicate seawater samples (each 60 ml) taken100 m apart at 0.3 m above the benthos by SCUBA divers at eachurchin-exclusion experimental reef within each zone on the 17, 19, 20of July 2012 for intermediate (North), high (West), and low (Southeast)nutrient input zones respectively. Samples were filtered, placed on iceto maintain a temperature below 5 °C during transport, and then storedat −20 °C (within 4 h of collection). Samples were analysed by theWater Studies Centre, School of Chemistry, Monash University forconcentrations of nitrogen (nitrogen-oxides and ammonia) and filter-able reactive phosphorus (FRP). Overall, standing nutrient concentra-tions were highest in the high nutrient input (West) zone, followed bythe intermediate nutrient input (North) zone, and lowest in the lownutrient input (Southeast) zone (Appendix A; Fig. A1a).

Light intensity and temperature were also assessed on the benthosusing three Hobo Pendant Temp-Light loggers fixed individually to star-pickets (separated by 100 m on each experimental reef), which loggedevery 5 min continuously from 1/04/2012 to 31/7/2012 at ~0.75 mabove the reef (at depths of 2.3 m, 3.4 m, and 3.7 m for West, North,Southeast zones respectively). Mean daily light intensity throughout theurchin-exclusion experiment revealed highest light intensity in the in-termediate nutrient input (North) zone, followed by the high nutrientinput (West) zone and was lowest in the low nutrient input (Southeast)zone (Appendix A; Fig. A1b). Mean sea temperature during the urchin-


3

exclusion experiment revealed similar temperatures ~13.5–14 °C, withthe coolest zone being the high nutrient input (West) zone, followed bythe intermediate (North) and low nutrient input (Southeast) zones,which were progressively warmer (Appendix A; Fig. A1c).

2.3.3. Data analysis of urchin-exclusion experimentDifferences in mean algal cover among treatments after 2 months

(to assess immediate macroalgal response) and at the 6 month com-pletion of the experiment were evaluated using 2-way ANOVA, with“Treatment” (2 levels: urchin-exclusion versus control) and “Zone” (3levels: high nutrient input (West), intermediate nutrient input (North),and low nutrient input (Southeast) zones as fixed factors and total coverof erect algae as the response variable.

To test the multivariate community response of all erect algal spe-cies (% cover) after 6 months, a fixed-effects two-way PermutationalMultivariate Analysis of Variance (PERMANOVA) (factors: urchin-ex-clusion “Treatment” and nutrient input “Zone”) was conducted on BrayCurtis similarity matrices (generated from square root transformeddata). For multivariate analysis, poorly resolved understorey algae and/or rare taxa were pooled into functional groupings, e.g. as filamentous/foliose reds, greens and browns. To visualise the multivariate analysis,canonical analysis of principal coordinates (CAP) was used to projectthe structure of the data with separation of “Treatment” and “Zone”factors guided by vector overlays indicating the relative contribution ofalgal taxonomic groups to the CAP ordination.

3. Results

3.1. Surveys of macroalgal cover and sea urchin abundance across zones

Surveys of canopy-forming algae as well as all erect macroalgaerevealed significant differences in cover among zones, with the highnutrient input (West) zone showing nil cover of canopy and minimalerect macroalgal cover, followed by low canopy and erect macroalgalcover for the intermediate nutrient input (North) zone, and highestcover of both macroalgal groups in the low nutrient input (Southeast)zone (Fig. 2a, Table 1a and b). The density and biomass of urchins alsoshowed a significant trend with highest abundances in the high nutrientinput (West) zone, intermediate abundance in the intermediate nutrientinput (North) zone, and lowest abundances in the low nutrient input(Southeast) zone (Fig. 2b, Table 1c and d). Macroalgal richness wassimilar in the high (West) and intermediate (North) nutrient inputzones (means of 4.33 and 4.67 macroalgal species per transect, re-spectively), but was ~3.5 times higher in the low nutrient input(Southeast) zone (mean of 15.83 macroalgal species per transect).PERMANOVA revealed significant separation of macroalgal commu-nities between zones (Zone: df= 2, SS= 15,678, MS= 7839, Pseudo-F= 3.16, P(perm) = 0.001, 998 unique perms.), with high (West) andintermediate (North) nutrient input zones not differing from each other(P= .60, 413 unique perms.), but both high (West) and intermediate(North) zones were significantly different from the low nutrient input(Southeast) zone (P(perm) < 0.01 for both pairwise comparisons, with408 and 412 unique perms. respectively) (Fig. 3).

3.1.1. Urchin-exclusion experiment across zonesSea urchins were successfully restricted (almost complete exclusion)

from octocoral urchin-exclusion plots in the high nutrient input (West)zone, while urchins were excluded completely from octocoral plots inthe intermediate (North) and low (Southeast) nutrient input zones(Fig. 4a; Table 2a). Factoring for the size of urchins (which variedacross zones), octocoral urchin-exclusion plots reduced overall biomassof grazing sea urchins relative to controls across all zones (Fig. 4b;Table 2b).

3.1.2. Macroalgal cover responseIn two of the three experimental zones, macroalgae immediately

bloomed in the urchin-exclusion plots relative to control plots acces-sible to grazing urchins (Fig. 5a–c; see Fig. 6 for example images). After2 months of urchin-exclusion, two-way ANOVA revealed a significant“Treatment by Zone” interaction effect on the cover of erect macroalgae(Table 3a). After two months, the high nutrient input (West) zoneshowed a strong immediate response in macroalgal growth (Fig. 5a; seeexample image, Fig. 6a), whereas intermediate algal growth was ob-served in the intermediate nutrient input (North) zone (Fig. 5b, 6b),while urchin-exclusion in the low nutrient input (Southeast) zone led tovery little algal growth (Fig. 5c, 6c), which generated the “Treatment byZone” interaction term (Table 3a).

Assessment of rates of biomass accumulation in urchin exclusionplots revealed high productivity in the high nutrient input (West) zonewhere 0.404 g Ulva (wet weight) ± 0.08SE week−1 was produced (i.e.

Fig. 2. Surveyed patterns in (a.) canopy and all erect macroalgal cover, and seaurchin abundance and biomass (b.) across the three different nutrient inputzones of Port Phillip Bay, data are means ( ± SE) of N = 6 survey reefs per zone(see Fig. 1), letters above bars indicate significant groupings within each bartype (see legend) at alpha = 0.05.

Table 1Results for 1-way ANOVA comparisons of macroalgal cover and sea urchinabundance and biomass as surveyed across three different nutrient input zonesof Port Phillip Bay (N= 6 reef transects per zone, see Fig. 1); (a.) cover ofcanopy-forming macroalgae, (b.) cover of all erect macroalgae, (c.) sea urchindensity, d) sea urchin biomass. Values in bold are significant at α = 0.05.

Transformation df MS F P

a.) Cover of canopy-formers (%)

Zone Y0.4 2 25.85 31.39 < 0.001Error 15 0.82

b.) Cover of erectmacroalgae (%)

Zone Y0.6 2 113.65 7.64 < 0.01Error 15 14.88

c.) Urchin density (m−2)Zone Y0.7 2 177.43 9.02 < 0.01Error 15 19.67

d) Urchin biomass (g m−2)Zone Y0.4 2 92.37 2.41 0.12Error 15 38.30


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equivalent of a 20 cm tall Ulva thallus after 3 months), followed byintermediate productivity in the intermediate nutrient input (North)zone 0.105 g Ulva (wet weight) ± 0.08SE week−1, and low

productivity in the low nutrient input (Southeast) zone at 0.001 g Ulva(wet weight) ± 0.00SE week−1 (e.g. Fig. 6a–c).

At the conclusion of the experiment after 6 months, differences inthe cover of erect macroalgae between the urchin-exclusion and back-ground ‘control’ increased in magnitude for both high nutrient input(West) and intermediate nutrient input (North) zones (Fig. 5a–b). After6 months, two-way ANOVA revealed a significant “Treatment by Zone”interaction (Table 3b). Tukey's post-hoc HSD revealed that urchin-ex-clusion in the high nutrient input (West) and intermediate nutrientinput (North) zones resulted in significant increases in macroalgal covercompared to background ‘control’ plots (Fig. 5a–b), while in the lownutrient input (Southeast) zone macroalgal cover in urchin-exclusionplots remained significantly lower than that observed in backgroundcontrol plots (Fig. 5c).

3.1.3. Macroalgal community responseComparison of macroalgal communities after 6 months revealed

differences between urchin-exclusion and background reef ‘control’plots, but which differed depending on nutrient input “Zone” (Table 4;Fig. 7). Pairwise comparisons revealed differences in macroalgal com-munity composition between urchin-exclusion and background controlplots for all zones, while comparison of control plots between the highnutrient input (West) and intermediate nutrient input (North) zoneyielded the only non-significantly different pairwise comparison(Table 4).

In the high nutrient input (West) zone, background control plotswere dominated by Ectocarpus sp. at 6 months (Fig. 7), while Ulva sp.dominated the urchin-exclusion plots (Fig. 7), which also revealedoverall higher algal richness and diversity (Table 5). In the intermediatenutrient input (North) zone, the background control algal communitywas dominated by filamentous green and red algae, whereas Ulva sp.and foliose red algae dominated the urchin-exclusion plots in this zone(Fig. 7), while algal richness and diversity was similar across treatmentsin this zone (Table 5). For the low nutrient input (Southeast) zone, thebackground control algal community was dominated by Sargassum spp.(Fig. 7), while foliose red algae dominated the community in urchin-exclusion plots (Fig. 7). However, reflecting the slow rate of algal co-lonisation, algal richness and diversity in urchin-exclusion plots re-mained lower than control plots by the 6-month conclusion of the ex-periment (Table 5).

4. Discussion

4.1. Macroalgal and sea urchin abundance across zones of productivity

Previous studies have shown that algal communities differ in re-sponse to variations in water quality or ‘bottom-up’ forces (Duarte,1995, Eriksson et al., 2002); however, rarely are algal communitiesexamined across different nutrient regimes in combination with re-plicated field experiments controlling ‘top-down’ effects of herbivory.

Fig. 3. Canonical analysis of principal coordinates ordination plot of macro-algal community composition as surveyed across the distinct nutrient inputzones of Port Phillip Bay; high nutrient input (West) zone = squares; inter-mediate nutrient input (North) zone = upward triangles; low nutrient input(Southeast) zone = downward triangles; n = 6 replicate reef transects per zone.Solid overlaid vectors indicate algae driving separation of community types(shorthand codes: Ecklonia_radi= Ecklonia radiata; Sargassum_decip= Sargassum decipiens; Sargassum_fall= Sargassum fallax). Bubble size re-presents 4 categories of percent cover of urchin barren occurring on eachtransect within each zone (see legend).

Fig. 4. Urchin-exclusion experimental treatment by (a.) urchin abundance, and(b.) urchin biomass attained for octocoral urchin-exclusion and control plots onexperimental barrens reef in each nutrient input zone of Port Phillip Bay. Dataare means ( ± SE) of N= 8 plots as summed across all sampling periods afterestablishment of the exclusion treatment.

Table 2Results of 2-way ANOVA testing the effects of the octocoral urchin-exclusion“Treatment” and nutrient input “Zone” on (a.) sea urchin abundance, and (b.)biomass. Values in bold are significant at α = 0.05.


a.) Urchin abundanceTreatment Y0.5 1 5.46 16.38 < 0.001Zone 2 29.17 87.46 < 0.001Treatment × Zone 2 0.69 2.07 0.14Error 42 0.33

b.) Urchin biomassTreatment Y0.5 1 66.75 19.26 < 0.001Zone 2 52.59 15.17 < 0.001Treatment × Zone 2 0.19 0.05 0.95Error 42 3.47


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The rarity of such investigations reflects the difficulty of simultaneouslyrunning field experiments manipulating herbivore-exclusions at mul-tiple locations in space. Using the octocoral Erythropodium hicksoni as anatural biological barrier (after Ling et al., 2019a), urchins were suc-cessfully and efficiently excluded from urchin barren grounds, enablingexploration of the observed counter-intuitive pattern of decliningmacroalgae and increasing urchin abundance across a gradient of in-creasing ‘bottom-up’ forcing of primary productivity across Port PhillipBay.

The novel use of octocoral urchin-exclusions across the gradient ofnutrient input obviated the logistical challenge of setting-up extensiveexperimental infrastructure and untenable maintenance schedulesacross multiple reefs. However, the spatial distribution of this naturalbarrier dictated the spatial design of the experiment. That is,

sufficiently large colonies were limited to only 3 of 4 zones of PPB andreplication across space within each nutrient input zone was limited.Nonetheless, the efficient use of this naturally available barrier pro-vided an opportunity to progress from logistically challenging fully-factorial experiments on single reefs (e.g. Kriegisch et al., 2019a,2019b) towards a more macroecological approach where experimentsare effectively distributed across environmental gradients (reviewed byBenedetti-Cecchi et al., 2018).

4.2. Macroalgal response to urchin-exclusion across zones

Intuitively, in the absence of grazing sea urchins, the most rapidresponse in macroalgal cover to urchin-exclusion from barren groundswas in the high nutrient input (West) zone of PPB. The intermediatenutrient input (North) zone followed suite and ranked second in termsof gross macroalgal response independent of herbivory. For the lownutrient input (Southeast) zone, the urchin-exclusion experiment re-vealed very little development of macroalgal cover in the exclusionplots, with algal cover in the absence of urchin grazing remaining lessthan the cover on the background reef after 6 months. This zone of PPBis closest to the open ocean with least impact of urban nutrient inputs,lowest overall nutrient concentrations, had lowest light levels at thebenthos during the experiment, yet intriguingly has the higheststanding cover of diverse perennial macroalgae. The rank of macroalgalproductivity across the nutrient input zones, as estimated from accu-mulated biomass of Ulva in urchin-exclusion plots, was consistent withobserved recovery rates of algal cover, with highest productivity in thehigh nutrient input (West), followed by the intermediate (North), withlowest productivity in the low nutrient input (Southeast) zone. That is,our overarching hypothesis that sea urchin grazing is capable of over-whelming macroalgal communities and causing barren grounds across asteep gradient in macroalgal productivity, was supported.

The results of our experiment accord with other studies in which theproductivity of algae has been observed to increase with artificial en-hancement of nutrient levels (e.g. Korpinen et al., 2007; Guarnieriet al., 2014; Tamburello et al., 2019; Kriegisch et al., 2019a,b). Forexample, Guarnieri et al. (2014) found that recovery of erect algaewould only occur when grazers were excluded, but was significantlyhigher in plots with added nutrients. This was also observed locally inkelp beds for the low nutrient input (Southeast) zone of PPB where kelpcover responded positively to nutrient enhancement, but which wasultimately overwhelmed by urchin grazing (Kriegisch et al., 2019a,b).Similarly, several studies report increased algal growth, particularlyamong fast-growing species, when nutrients are enhanced (e.g. Duarte,1995; Campbell, 2001; Bokn et al., 2003; Ghedini et al., 2015). Thisnotion corroborates with the patterns of algal communities found in thehigh nutrient input (West) and intermediate (North) zones of PPB thatare dominated by fast growing opportunistic ephemeral species, such asUlva sp. (e.g. Campbell, 2001), in contrast to the low nutrient input(Southeast) zone, where Sargassum spp. and kelp Ecklonia radiata arethe dominant species (Fig. 7), which grow relatively slowly but formpersistent perennial macroalgal canopies.

4.3. Macroalgal community response

In the high nutrient input (West) and intermediate (North) zones,but not the low nutrient input (Southeast) zone, macroalgal communitystructure differed between urchin-exclusion and control plots. In thehigh and intermediate nutrient input zones, the algal community in thecontrol plots, accessible to urchins, was composed of a sparse macro-algae but which was dominated by Colpomenia sp., whereas the urchin-exclusion plots were dominated by a dense cover of Ulva sp. (Fig. 5a).Typically, high nutrient inputs stimulate the growth of foliose specieslike Ulva sp. (Lobban and Harrison, 1994; Campbell, 2001), but thehigh palatability of such algae makes it susceptible to overgrazing by

Fig. 5. Percentage cover of erect macroalgae through time in the octocoralurchin-exclusion treatment and controls on barren grounds across the threenutrient input zones of Port Phillip Bay; (a.) high nutrient input (west) zone;(b.) intermediate nutrient input (north) zone; (c.) low nutrient input (southeast)zone. Data are means ( ± SE) of N = 8 plots, asterisks indicate significanttreatment differences tested within zones at alpha = 0.05, tested at 2 and6 months.


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urchins (Cyrus et al., 2015). In the low nutrient input (Southeast) zone,the exclusion of urchins revealed minimal development of algae after6 months, at which point algae had not even attained background levelson the reef accessible to urchins. Thus, for this low nutrient input/ lowproductivity zone, urchin-exclusion over > 6 months appears necessaryfor algal communities to recover towards the perennial assemblagecharacterising reefs within this zone.

Despite the low rate of macroalgal productivity in the low nutrientinput (Southeast) zone, the macroalgal diversity here was the highest.Macroalgal richness was negatively correlated with increasing pro-ductivity across PPB, increasing from a mean of 4.33 species (per1.25 m2) in the high productivity (West) zone, to 4.67 in the inter-mediate productivity (North) zone, to a maximum richness of 15.83 inthe low productivity (Southeast) zone. Thus, in accordance with ob-servations of other studies (Worm et al., 1999; Gorgula and Connell,2004), the most diverse algal communities in our study were also ob-served to occur in the lowest nutrient regime. While maximum mac-roalgal diversity and high coverage of intact kelp beds were associatedwith low nutrient input/ low algal productivity, exclusion of seaurchins realised increases in algal diversity regardless of local algalproductivity across Port Phillip Bay.

4.4. Reconciling top-down and bottom-up

Collectively, our survey and experimental results revealed the ‘top-down’ capacity for destructive urchin grazing, in terms of urchin bio-mass, to be greatest where algal productivity (i.e. bottom-up forcing)was also greatest (as also reported in the mesocosm experiment ofGhedini et al., 2015). This result therefore contradicts the notion thatimpacts of herbivores will be largest where primary production is low.Intriguingly, while oligotrophic reef systems may be considered parti-cularly vulnerable to urchin overgrazing (e.g. Boada et al., 2017),bottom-up forcing on the urchin populations themselves has rarely beenconsidered. Instead, studies of urchin population dynamics are typicallyfocussed on supply-side processes governing recruitment/ settlementand top-down predatory control (reviewed by Ling et al., 2015). Per-haps the unique persistence of highly abundant urchin populations and

Fig. 6. Examples of the immediate 2-month response ofmacroalgae to urchin-exclusion using “octocoral plots” (a. –c.) relative to background “control plots” accessible to grazingsea urchins (d. – f.) across the different nutrient input zones ofPort Phillip Bay. Inner strings attached to steel frame define a200 mm by 200 mm plot; relative size of urchins in each zoneis apparent in the controls for each respective zone (d., e., f.).

Table 3Results of 2-way ANOVA testing the effects of “Treatment” (octocoral urchin-exclusion vs control) and nutrient input “Zone” on cover of macroalgae after(a.) 2 months, and (b.) 6 months of the experiment on barren grounds acrossPort Phillip Bay. Values in bold are significant at α = 0.05.


a) 2 monthsTreatment Y0.25 1 2.01 8.59 < 0.01Zone 2 0.11 0.47 0.63Treatment × Zone 2 1.97 8.44 < 0.001Error 42 0.23

b) 6 monthsTreatment Y0.25 1 5.43 12.68 < 0.001Zone 2 3.67 8.57 < 0.001Treatment × Zone 2 9.40 10.98 < 0.001Error 42 0.43

Table 4Results of 2-way PERMANOVA testing the effects of “Treatment” (octocoralurchin-exclusion vs control) and nutrient input “Zone” on macroalgal com-munities after 6 months of the experiment on barren grounds across Port PhillipBay. Analyses were run on Bray-Curtis similarity matrices following square roottransformation of percent cover algal data. Factors highlighted in bold aresignificant at α = 0.05; pairwise tests detail the source of the significant“Treatment” by “Zone” interaction.

Source df MS F P (perm) Unique perms

Treatment 1 13,186 8.71 < 0.001 997Zone 2 15,026 9.92 < 0.001 999Treatment × Zone 2 6267 4.14 < 0.001 998Error 42 1513

Pairwise tests Zone t P(perm) Unique permsExclusion vs Control West 2.01 0.013 917

North 2.68 0.002 907Southeast 2.28 0.001 921

Exclusion West vs North 1.73 0.048 902West vs Southeast 3.23 0.002 938North vs Southeast 2.87 0.002 897

Control West vs North 1.52 0.072 915West vs Southeast 3.54 0.002 912North vs Southeast 2.79 0.001 928


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the high persistence-stability of barren grounds themselves, wherebyurchin populations switch diet and even demonstrate carnivory to avoid‘eating themselves out of house and home’ (e.g. Ling et al., 2019b), hasled to perceptions that urchin populations are largely decoupled fromprimary production. Nonetheless, here our results indicate couplingbetween secondary ‘urchin’ production and primary ‘macroalgal’ pro-duction, as is also suggested by patterns at global scales where thecarrying capacity of urchin biomass appears correlated with regionalprimary productivity. For example, high urchin biomass occurs alongthe highly productive Pacific Northwest which contrasts strongly withlow urchin biomass occurring within the oligotrophic Mediterraneansystem (Ling et al., 2015; Boada et al., 2017). While barren groundsform along both these eutrophic and oligotrophic coasts, the intensityof bottom-up and top-down forcing would appear necessarily amplifiedon coasts with higher primary productivity. Furthermore, systems ofthe Pacific Northwest appear far more dynamic in space and time thanthose in the Mediterranean (S. D. Ling pers. obs.), with our resultssuggesting that the ‘top-down’ effect of grazing will be more pro-nounced where ‘bottom-up’ forces drive high primary productivity butdually facilitate the accumulation of large urchin biomass towards acritical tipping-point of overgrazing.

Ultimately, while urchin grazing impacts could be the same acrosssystems in terms of collapsing local standing macroalgae (Ling et al.,2015), the tipping point required for overgrazing has been reported tobe lower for oligotrophic systems (Boada et al., 2017). In Port PhillipBay, we conducted an experiment to define overgrazing and recovery

tipping-points within the intermediate nutrient input (northern) zone,to reveal that the tipping-points were not influenced by a local doublingof nutrient concentrations (Kriegisch et al., 2016). Intriguingly, basedon our current findings and that of Boada and colleagues (2017), per-haps differences in tipping-points may have been observed if the ex-periment was run in the lowest nutrient input zone of PPB where adoubling in nutrients may have surpassed a critical threshold in mac-roalgal production. Thus, it remains unclear how the non-linear dy-namics of urchin overgrazing are altered by changes in primary pro-ductivity, which is itself likely non-linear and perhaps dependent onrelative changes across the oligotrophic-eutrophic spectrum. Also, itremains unclear how the interacting effects of shifts in macroalgal di-versity (including palatability) may also mediate phase-shift dynamicsfor this temperate reef system (Reeves, 2017).

5. Conclusions

Examination of the relative strengths of top-down and bottom-upcontrol for subtidal reefs in Port Phillip Bay revealed sea urchinabundance to be positively correlated with increasing nutrient avail-ability and algal productivity but negatively correlated with standingbiomass of algae. Thus, the ‘top-down’ capacity for destructive over-grazing by sea urchins was observed to be highest where algal pro-ductivity (i.e. bottom-up forcing) was also greatest. Intriguingly, thisfinding appears counter to perceptions that herbivores will havegreatest impact on standing primary producers where primary pro-ductivity is lowest. Our results therefore suggest that urchin biomass isat least partly driven by local primary production, as opposed to beingdecoupled from it. We also observed greatest macroalgal diversity andgreatest coverage of intact kelp beds to be associated with low algalproductivity and exclusion of urchins realised increases in algal di-versity regardless of local productivity. The ecological implications ofour results are that increases in bottom-up forcing, due to anthro-pogenic nutrient inputs, can amplify macroalgal/urchin barrens phase-shifts. Thus, in the absence of functional predators capable of dam-pening urchin populations and their ‘top-down’ control of kelp beds(e.g. Shears and Babcock 2002; Pederson and Johnson, 2006; Linget al., 2009, 2019b), our results indicate that increasing nutrification ofcoastal areas will also likely amplify the risk of kelp bed overgrazing

Fig. 7. Canonical analysis of principal coordinates ordination plot based on algal community composition for each combination of treatment after 6 months forurchin-exclusion versus background ‘control’ (see legend for symbols, stress = 0.19). Circle adjacent to ordination plot identifies vectors of algal species contributingmost to differentiation of ordination groups, i.e. longer vectors indicate greater contributions (algal codes are: sar= Sargassum sp.; und=Undaria pinnatifida;ulva=Ulva sp.; cod= Codium fragile; col. = Colpomenia peregrina; ecto= Ectocarpus sp.; fil_br = unidentified filamentous browns; fil_red= unidentified filamentousreds; fil_gr= unidentified filamentous greens; dictyop=Dictyopteris muelleri; ste= Stenogramme interrupta; cau= Caulerpa sp.; zon = Zonaria sp.; dis=Distromiumflabellatum).

Table 5Mean macroalgal richness and diversity by nutrient input “Zone” and“Treatment” (octocoral urchin-exclusion vs control) after 6 months of the ex-periment on barren grounds across Port Phillip Bay. Data are means of N = 8plots.

Zone Treatment Algal Richness Shannon Diversity H′(loge)

High (West) Control 4.13 1.00High (West) Exclusion 5.00 1.05Intermediate (North) Control 3.13 0.80Intermediate (North) Exclusion 3.25 0.70Low (Southeast) Control 4.25 1.16Low (Southeast) Exclusion 3.25 0.74


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and cascading transitions to dominance by fast-growing opportunisticand problematic algae such as turfs that would otherwise be out-competed by kelps (Kriegisch et al., 2016; Kriegisch et al., 2019a,b;Filbee-Dexter and Wernberg, 2018; Reeves et al., 2018). Finally, whilebottom-up forcing on algal productivity clearly plays an important rolein structuring temperate reef communities, our surveys and criticalexperimentation demonstrates that the ‘top-down’ effect of sea urchinsis indeed capable of keeping pace and controlling reef communitiesacross a gradient in algal productivity.

Declaration of Competing Interest

The authors declare no conflict of interest.

Acknowledgements

This study was supported by a Victorian State GovernmentDepartment of Environment Land Water and Planning grant to CRJ andS. Swearer ("The Reef Ecosystem Evaluation Framework"), AustralianPostgraduate Awards to NK and SER, Holsworth Wildlife Endowmentsto NK, SER and SDL (104121; 104624), plus Australian ResearchCouncil funds to SDL (DP170104668). SDL and NK developed the ex-perimental methods and designed the research. SDL, NK and SER per-formed all field sampling; SDL and NK analysed data and wrote themanuscript; all authors provided edits. Sea urchins were collectedunder the Victorian Department of Primary Industries, Fisheries Act1995 Permit RP1084 issued for 29 May 2012 to 28 May 2015.

Appendix A. Macroalgal growth conditions present in each of the nutrient input zones of Port Philip Bay during the urchin-exclusionexperiment

Fig. A1. Environmental conditions of (a) nutrient concentration, (b) mean daily light intensity, and (c) mean temperature measured on the seafloor at the urchin-exclusion reefs in each nutrient input zone during the experimental period. Data are means ( ± SE) of N= 3 water samples for nutrient analysis taken 100 m apart on17, 19 & 20 July 2012 in the North, West and Southeast zones respectively; and mean daily light/ temperature from a single data logger on each experimental reeflogging at a frequency of every 5-min from 1 April to 31 July 2012.


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Sea urchin control of macroalgal communities across a productivity gradientIntroductionMaterials and methodsStudy systemSurveys of macroalgal cover and sea urchin abundance across zonesUrchin-exclusion experiment across zonesAssessment of macroalgal responseNutrient, light and temperature conditions during the urchin-exclusion experimentData analysis of urchin-exclusion experiment

ResultsSurveys of macroalgal cover and sea urchin abundance across zonesUrchin-exclusion experiment across zonesMacroalgal cover responseMacroalgal community response

DiscussionMacroalgal and sea urchin abundance across zones of productivityMacroalgal response to urchin-exclusion across zonesMacroalgal community responseReconciling top-down and bottom-up

Conclusionsmk:H1_20AcknowledgementsMacroalgal growth conditions present in each of the nutrient input zones of Port Philip Bay during the urchin-exclusion experimentReferences

journal of experimental marine biology and ecology · australia; large filled-symbols in the...

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