the effect of artificial defaunation on bacterial assemblages of intertidal sediments

y and Ecology 337 (2006) 147–158www.elsevier.com/locate/jembe

Journal of Experimental Marine Biolog

The effect of artificial defaunation on bacterial assemblagesof intertidal sediments

Eileen T. Stocum a, Craig J. Plante b,⁎

a Biology Department, College of Charleston, Charleston, SC 29401, United Statesb Grice Marine Laboratory, 205 Fort Johnson, Charleston, SC 29412, United States

Received 3 January 2006; received in revised form 26 April 2006; accepted 14 June 2006

Abstract

The use of the artificial defaunation of sediments is widespread among studies examining the disturbance and recovery ofbenthic macrofaunal communities. Standard methods of defaunation include driving the sediment to anoxia, freezing and sieving.In this study we performed a field experiment to test the assumption that the bacterial assemblages are unaffected by these methodsof defaunation. Same-sized patches of sediment were defaunated by covering sediment with plastic sheeting (weighted by concreteblocks), freezing or sieving (1-mm mesh). Macrofaunal counts of sediment cores, taken to determine the effectiveness of eachdefaunation method, indicated that although none of the treatments removed 100% of macrofauna, all resulted in reducedmacrofaunal presence, with the sieved treatment being the most effective. Bacterial samples were taken over the course of a monthto determine both the initial and long-term effects of defaunation on bacterial community structure. Numerical effects weredetermined via epifluorescence microscopy, whereas differences in community composition were followed using PCR anddenaturing gradient gel electrophoresis (DGGE). The anoxic treatments resulted in significant numerical changes in both active andtotal cell counts over time, while the frozen and sieved treatments caused less apparent changes. All of the treatments initiallychanged the composition of the community; however, anoxic and sieved treatments resulted in subtle changes while the frozentreatment produced more notable and variable changes within the community. The composition of the bacterial community in all ofthe treatment plots trended towards recovery, or convergence towards that of ambient sediments, by the t=25-day sampling period.© 2006 Elsevier B.V. All rights reserved.

Keywords: Bacteria; Benthic; Defaunation; Macrofauna; Recolonization

1. Introduction

Over the past three decades, theoretical advances andfield experiments have led to the recognition that marinecommunities can be structured in a non-equilibriumfashion, by the interactions of the heterogeneity of the

⁎ Corresponding author. Tel.: +1 843 953 9187; fax: +1 843 9539199.

E-mail address: [email protected] (C.J. Plante).

0022-0981/$ - see front matter © 2006 Elsevier B.V. All rights reserved.doi:10.1016/j.jembe.2006.06.012

physical–chemical environment, disturbance, and recruit-ment (e.g., Dayton, 1971; Reice, 1994; Sousa, 2001). Theeffect of disturbance, recolonization and succession on thecommunity structure of sediment-dwelling invertebrateshas been amajor focus in soft-bottom habitats (e.g., Smithand Brumsickle, 1989; Gamenick et al., 1996; Thrushet al., 1996). Studies of recovery in these habitats com-monly employ experimental defaunation. Standard defau-nation methods include driving the sediment to anoxia(Gamenick et al., 1996; Thrush et al., 1996), freezingsediment (Shull, 1997; Hall and Frid, 1998), and

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148 E.T. Stocum, C.J. Plante / Journal of Experimental Marine Biology and Ecology 337 (2006) 147–158

removing macrofauna by sieving (Kristensen and Black-burn, 1987; Gilbert et al., 1994). Each of these methodsalters the physico-chemical attributes of the habitat,making it important to understand the effects of eachmanipulation not only on macrofauna, but also on thesedimentary matrix and benthic microbiota. Bacterialdensities and compositions have been shown to influenceinvertebrate larval settlement (Keough and Raimondi,1995; Unabia and Hadfield, 1999; Olivier et al., 2000),and benthic bacterial biomass can contribute significantlyto the diet of marine macrofauna (Amon and Herndl,1991), with indications that diverse bacterial strains differin their susceptibility to digestion (e.g., Plante andShriver, 1998). In addition, microbial secretions haveimportant impacts on sediment stability (Madsen et al.,1993; Yallop et al., 2000). Despite the varied roles ofbacteria in the recruitment and subsequent populationdynamics of soft-bottom invertebrates, few studies(Findlay et al., 1990a) have explicitly considered thepotential effects of these defaunation protocols on benthicbacterial communities.

Response of the benthic bacterial community to biotic(Bianchi and Levinton, 1981; Findlay and White, 1983;Walters and Moriarty, 1993; Aller and Yingst, 1985;Findlay et al., 1990b) and abiotic (Alongi, 1985; Findlayet al., 1990a; Freitag et al., 2003) disturbances has beenaddressed in previous studies. Mechanical disturbance(e.g., sieving), for instance, typically has led to metabolicshifts and initial reduction of biomass of sedimentarybacteria, followed by return to pre-disturbance levelswithin days after the disturbance (Findlay et al., 1990a,b;Langezaal et al., 2003). Freezing of soil can result inbacterial mortality, and thereby alter abundances andactivities (e.g., Pesaro et al., 2003), while chemicalchanges in the environment (e.g., anoxia) likewise canaffect bacterial densities and activity levels (Harveyet al., 1995; Freitag et al., 2003). The potential fordisturbances to change the composition of the bacterialcommunity, for instance by sieving, anoxia or freeze–thaw events (Findlay et al., 1990b; Freitag et al., 2003;Sharma et al., 2006, respectively), has also beendemonstrated.

Here we test the assumption that common methods ofexperimental defaunation have no qualitative or quanti-tative effects on benthic bacterial communities. Numer-ical changes were monitored by performing direct countsvia epifluorescence microscopy, and bacterial communitychangeswere detected using PCR and denaturing gradientgel electrophoresis (DGGE). These techniques were usedto compare field samples of ambient and artificiallydefaunated (asphyxiated, frozen, or sieved) sedimentsover the course of 25 days.

2. Methods

2.1. Study site

The study was conducted on an intertidal sandflat inGrice Cove, Charleston Harbor (32° 46′N, 79° 55′W),South Carolina, USA. Grice Cove experiences semi-diurnal tides with an annual range of 2.9 m; water tem-peratures ranged from14.4 to 20.1 °C during the course ofthe study (March–April 2003). The study site consisted ofan area of coarse-grained (sand and shell fragments)beach that gradually slopes down to a flat area of finersand (medium grain size 226 μm), which is fully exposedat most low tides. The flat area, where the experimentalunits were located, extends ∼50 m offshore. Mud snails(Ilyanassa obsoleta) were the most obvious and abundantepifauna.

2.2. Experimental design

Same-sized (0.16 m2) patches of sediment weredefaunated by asphyxiation, freezing, or sieving.Treatment plots that were driven to anoxia were coveredwith black plastic sheeting (∼0.1 mm thick), weightedby 0.16 m2, 25 kg concrete blocks, for 12 days. Prior toinitiation of the experiment we collected sediment (fromtop 0.2 m) and treated by either freezing or sieving.Frozen treatment sediments were placed at −40 °C for48 h, and then stored at 4 °C until placement in the field(2–4 days). Sieved treatment sediments were passedthrough 1-mmmesh and stored at 4 °C until placement inthe field (2–4 days). At the initiation of the experiment (6March 2003), the upper 0.2 m of sediment from∼0.16 m2 plots was removed and replaced with theappropriate “treatment” (frozen or sieved) sediment.Quadrats of ambient sediment were also designated atthis time to serve as controls for the duration of the study.Treatment plots were randomly dispersed (at a tidalheight of ∼0.6 m) and marked with flags throughout anarea ∼100 m2, with no plot positioned within 2 m ofanother. Following wave-induced and other losses, thefinal number of replicates was as follows: 5 frozen andambient, 4 sieved, and 3 anoxic.

2.3. Macrofaunal counts

To determine the effectiveness of our defaunationtreatments, we took cores of each of the plots at 0 and16 days during exposure at low tide. Cores were taken at2 depths, 0 (surface) to 0.1 m and 0.1 m to 0.2 m, using anopen-ended cylinder 0.1 m in diameter (volume of eachcore section=785.4 cm3). The position of coring within

149E.T. Stocum, C.J. Plante / Journal of Experimental Marine Biology and Ecology 337 (2006) 147–158

the treatment plot was determined via a randomized gridsystem, ensuring that no area was sampled twice. No corewas taken within 0.02 m of the edge of the treatment plot.As described by Thrush et al. (1996), core holes werefilled with sediment previously defaunated by the samemethod as the cored plot (e.g., frozen treatment core holesrefilledwith previously frozen sediment). Coreswere thensieved using 1-mm mesh and collected macrofauna werefixed in 4% buffered formalin. Macrofauna were sortedunder a dissecting microscope and identified to order orclass.

2.4. Microbial sampling

Samples for enumeration and molecular analysis ofbacterial communities were collected on 6 occasions(t=0, 1, 2, 10, 16 and 25 days). For bacterial counts, 1–2 gof surface sediment was collected via spatula and placedin tubes containing 20 ml of sterile (autoclaved andfiltered, 0.2 μm) seawater. Within 2 h of collection, allsamples were sonicated for 20 s at 65 W (according toprevious optimization experiments; Wilde and Plante,2002) using a 3-mm sonic probe (Branson UltrasonicsCorp., Danbury, CT), and aliquots (2 ml) were transferredto sterile 15-ml tubes. Metabolically active bacteria werestained with 5-cyano-2,3-ditoyl tetrazolium chloride(CTC; Polysciences Inc., Warrington, PA), which acts asan artificial electron acceptor in the electron transportsystem indicating oxidative cell metabolism. CTC (180 μlof 25mm)was added to each tube and incubated for 3 h at25 °C in the dark while shaking. Samples were then fixedin formalin (2% final concentration). Fixed samples werecentrifuged at 4000×g for 15 min and resuspended inTrizma buffer (0.05 M, pH 8.10); Triton X-100 (20 μl of0.5%) was added, samples were placed on ice for 20 min,then sonicated (20 s with 3-mm sonic probe, 65 W). Tostain the remaining bacteria, 4′,6-diamino-2-phenylindole (DAPI, 100 μl/ml; Sigma, St. Louis, MO) wasadded to samples, which were incubated for 20 min at25 °C in the dark, while shaking. Prior to slide prepa-ration, samples were stored at 4 °C. Samples were con-centrated onto black polycarbonate membranes (0.22 μm,25 mm). The remaining sample was then dried (60 °C for>48 h) to allow normalization to dry sediment (Wilde andPlante, 2002).

Active and total counts were made from each slideusing a Nikon epifluorescence microscope at 1250×magnification. DAPI-staining bacteria were countedusing a UV filter set (Omega XFO2, 330WB80 exciter,400EFLP emitter). CTC-staining (active) bacteria werecounted using a rhodamine filter set (Omega 605DF55,center wavelength 605 nm, discriminating filter, full

band width at half maximum transmission 55 nm). AsCTC stain interferes with DAPI (Yu et al., 1995), totalcell counts were taken as the sum of CTC and DAPIcounts. For each slide >300 cells/slide, or 20 randomlychosen fields, were counted.

Surface sediment for molecular analysis was collectedvia spatula (∼0.5 g) and placed into bead-beater vials(2ml conical microtubes) containing ∼2.5 g of 0.1 mmsilica/zirconia beads (Biospec Products, Battlesville, OH).Samples were stored at −20 °C until extraction. Bacterialcells were physically lysed using bead-mill homogeniza-tion (Mini Beadbeater-8, Biospec Products). All sampleswere extracted via a standard phenol:chloroform extrac-tion, with final purification using the Wizard PCR DNApurification system (Promega, Madison, WI, USA)(Plante and Wilde, 2004). PCR was performed using theprimer set for amplification of the V3 region (5′-ATTACCGCGGCTGCTGG-3′ and 5′-CGCCCGCCGCGCGCGGCGGGCGGGGCGGGGGCAGGGGGGCTACGGGAGGCAGCAG-3′) of the 16S rRNA gene,according to conditions used by Plante andWilde (2004).

When necessary, PCR products were concentratedusing an ethanol precipitation. Four 50 μl reactionswere added to an equal volume of ice-cold 100%isopropanol and stored at −20 °C overnight. DNA waspelleted by centrifugation (10 min, 16,000×g, at 4 °C),rinsed with 750 μl cold 70% ethanol, and recentrifuged(5 min, 16,000×g, at 4 °C). EtOH was removed via avacuum centrifuge (25 °C) and pellets were resus-pended in 50 μl TE buffer, resulting in an approxi-mately four-fold concentration. The products of allconcentrations were checked on a 1% agarose gel.DNA was then quantified fluorometrically using thePicoGreen dsDNA Quantitation kit (Molecular Probes,Eugene OR, USA) according to manufacturer'sinstructions.

Denaturing gradient gel electrophoresis (DGGE),which separates similarly sized DNA fragments on thebasis of sequence, was used to obtain a “fingerprint” ofthe bacterial community of each sample. An 8%polyacrylamide gel with a gradient of DNA denaturingagent was cast by mixing solutions of 40 and 60%denaturing agent (100% denaturant is 7 M urea and 40%deionized formamide). Each lane was loaded withapproximately the same amount of DNA (300 ng). Thegel was run at 70 V for 17 h at 60 °C in 1× TAE buffer(40 mm Tris [pH 7.4], 20 mm sodium acetate, 1 mmEDTA). Gels were stained with 1× SybrGold (MolecularProbes) for 30 min and visualized under UV light in aModel 1000 VersaDoc imaging system (Bio-RadLaboratories, Hercules CA, USA) (Plante and Wilde,2004).

Table 1Mean macrofaunal numbers of both coring depths for all treatments at 0 and 16 days

Treatment Anoxic Frozen Sieved Ambient

Core depth (m) 0–0.1 0.1–0.2 0–0.1 0.1–0.2 0–0.1 0.1–0.2 0–0.1 0.1–0.2

t=0 dayGastropoda 0.0 0.0 1.4 2.5 0.0 0.0 4.4 0.0Amphipoda 0.3 0.3 0.0 0.5 0.0 0.0 0.2 0.0Isopoda 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0Decapoda 0.0 0.0 0.6 1.0 0.0 0.0 0.0 0.0Polychaeta 1.8 1.3 1.8 0.3 5.0 0.0 3.6 2.8Oligochaeta 0.0 0.3 0.2 0.0 0.0 0.0 0.4 0.4

t=16 daysGastropoda 0.0 0.0 0.8 1.0 0.0 0.0 0.0 0.0Amphipoda 0.0 0.2 0.6 0.6 0.3 0.0 0.4 0.2Isopoda 0.0 0.2 0.0 0.0 0.3 0.0 0.2 0.0Decapoda 0.0 0.0 0.2 0.0 0.0 0.0 0.0 0.2Polychaeta 3.4 1.6 0.4 0.0 0.8 3.0 5.0 3.5Oligochaeta 0.0 0.0 0.0 0.0 0.0 0.0 0.2 0.0

Counts are displayed as # macrofauna per core section.


Replicates of 0 day samples were analyzed via DGGEto determine the initial effects of each treatment on thebacterial community of the experimental units. We alsoexamined the recovery of the community in each treat-ment by analyzing 3 sampling periods (0, 1, 25 days) viaDGGE. These sampling points were chosen afterpreliminary analysis indicated that the most notablechanges in the bacterial communities were detected dur-ing these sampling periods.

2.5. Data analysis

Total numbers of macrofauna were analyzed using atwo-way ANOVA to detect the effects of treatment(anoxic, frozen, sieved) and time. Likewise, active andtotal cell counts were analyzed using two-way ANOVA.We also used one-way ANOVA to detect differenceswithin treatments over time andwithin time periods due totreatment. All pairwise comparisons were done using theTukey HSD correction. Prior to analysis, outliers wereexcluded using Dixon's test (95% confidence limit; Sokaland Rohlf, 1995); all data were tested for homogeneity ofvariance (Levene's test) and natural log transformed asrequired. Statistical analyses were done using thestatistical software JMP version 5.01 (SAS Institute,Cary, NC) or SYSTAT version 5.2 (SPSS, Chicago, IL).Quantity One software (Bio-Rad) was employed forDGGE gel acquisition and analysis. After removingbackground intensity from all lanes (via the rolling diskmethod), the software detects different bands, theirdensity in the lanes, and matches them to similar bandsin other lanes on the same gel. Using these lane profiles

the software generates a similarity matrix based oncomparisons of band pattern (i.e., unweighted compar-isons), via the method of the Dice Coefficient. From thisbinary matrix, a distance matrix was calculated. The dis-tance matrix was then analyzed by nonmetric multidi-mensional scaling (NMDS) (van Hannen et al., 1999).

3. Results

3.1. Macrofaunal numbers

Macrofaunal counts (Table 1) of the top 0.1 m of thecore indicated that the effects of treatment were sig-nificant (P<0.001) but changes due to time andthe treatment* time interaction were not significant(P=0.406 and 0.206, respectively). Likewise, counts ofthe whole core indicated that the effect of treatment wassignificant (P<0.001) but changes due to time or theinteraction of treatment* time were not significant(P=0.809 and 0.174, respectively). Counts of the top0.1 m of 0 day anoxic cores showed a significant differ-ence as compared to ambient (P=0.015). At 16 days,counts of the top 0.1 m of anoxic samples were notsignificantly different from ambient sediment (P=0.845).Whole core counts of anoxic or frozen samples did notshow significant differences from ambient at any timeperiod; however, at 16 days, whole core counts of frozensamples showed a trend towards significance as comparedto ambient (P=0.094). The top 0.1 m of the frozen coredid not differ significantly from ambient at 0 or 16 days(P=0.140 and 0.314, respectively). The top 0.1 m ofsieved samples showed significantly lower counts as

Fig. 1. Mean density of active (CTC-stained) bacteria over time foranoxic (A), frozen (F), sieved (S) macrofaunal removal treatments, andambient sediments (N). Error bars are not included for clarity.

Fig. 2. Mean density of total bacteria over time for anoxic (A), frozen(F), sieved (S) macrofaunal removal treatments, and ambientsediments (N). Error bars are not included for clarity.


compared to ambient sediment at 0 day but not at 16-daysampling times (P=0.002 and 0.185, respectively).Likewise, whole core counts of the sieved samplesshowed significant differences as compared to ambient at0, but not at 16 days (P=0.006 and 0.230, respectively).

3.2. Bacterial numbers

Active cell densities showed a significant differ-ence due to time (P<0.001) and due to treatment* time(P=0.010) (Fig. 1). There was a trend towards signifi-cance due to treatment (P=0.076), primarily because ofdifferences between the anoxic and frozen treatments ascompared to ambient sediments (P=0.014 and 0.077,respectively; Fig. 1). The three experimental treatmentsshowed an apparent initial, short-lived increase innumbers of active bacteria, although differing somewhatin degree and timing. Temporal changes were highlysignificant for both anoxic and frozen treatments(P=0.002 and <0.001, respectively), with significant in-creases between 0 day vs. 1, 2, and 10 days, andsignificant decreases between 10 days as compared to 16and 25 days for both treatments (P<0.05 for all).Although the overall effect of time was not significantwithin the sieved treatment, the pairwise comparisons of1 day vs. 16 and 25 days samples were significant(P=0.049 and 0.028, respectively). Likewise, time wasnot a significant effect for the ambient sediment(P=0.236), but the 1 day vs. 10 days comparison wassignificant (P=0.026). At a given sampling date,treatments varied significantly from one another only at1 day, with ambient sediments significantly lower than theanoxic (P=0.001), frozen (P=0.009), and sieved

(P=0.013) treatments. P values ranged from 0.103 to1.000 for all other between-treatment comparisons at allother sampling dates.

Total cell counts showed a significant time effect(P<0.001) with strong increases up to 10 days, followedby rebound toward original densities for all treatments(Fig. 2). There were no significant differences detecteddue to treatment (P=0.583) or to the treatment* timeinteraction (P=0.618). For all four treatments, totalbacterial numbers at 10 days were significantly higherthan at 0, 1, 16 and 25 days (P<0.05 for all). Samplestaken at 2 days also differed significantly from 10 days, ortrended toward significance, for the ambient sediments,frozen and sieved treatments (P<0.10), whereas the 2-dayand 10-day samples did not differ in the anoxic samples(P=0.948). At a given sampling date, between-treatmentcomparisons approached significance only at 1 day, withambient sediments lower than the anoxic (P=0.056),whereas no other between-treatment comparisons weresignificantly different at 1 day, or at any other samplingtime (P>0.129 for all).

3.3. Composition of bacterial assemblages

Three sets of replicates were analyzed via DGGE toassess relative bacterial diversities and to detect differ-ences (relative to ambient sediment control) in thebacterial community composition at the initiation of theexperiment (t=0 day). Numerous bands (25–30) indicat-ed a diverse bacterial assemblage in all treatments, andthere was no statistical difference in band number amongtreatments (P=0.944, ANOVA). Whereas the majority ofbands were common to all treatments, notable exceptions

Fig. 3. Representative (A) DGGE gel and (B) MDS plot of 0-day replicates showing effects of defaunation protocols on bacterial communitycomposition. A = anoxic, F = frozen, S = sieved, N = ambient treatments.


were seen, particularly in the frozen treatment (Fig. 3A).Freezing had the greatest compositional effect on thebacterial community, sieving had less of an effect, and

Fig. 4. Representative (A) DGGE gel and (B) MDS plot showing recovery offrozen, S = sieved, N = ambient treatments, ● = 0 day, ○ = 1 day, ▾ = 25

anoxia the least (Fig. 3B). Similarity values betweenambient and frozen sediment ranged from 80.8 to 93.1%,as compared to between-replicate similarities for frozen

bacterial communities following defaunation protocols. A = anoxic, F =days. Arrows indicate changes in community from 0 to 25 days.


samples averaging 90.3%. Similarity values betweenambient and sieved sediment ranged from 83.6 to 93.1%,as compared to between-replicate values of 89.2%. Am-bient and anoxic sediments had similarity values thatranged from 89.3 to 98.1%, compared to between-repli-cate values averaging 90.6%. When between-treatmentdissimilarity values were compared to within-treatment(replicate) values, only the frozen vs. ambient sedi-ment control comparison trended toward significance(P=0.063), while sieved (P=0.641) and anoxic(P=0.359) treatments were indistinguishable from ambi-ent sediments.

Two sets of replicates were analyzed via DGGE(Fig. 4A) to follow the recovery of the bacterial com-munity (i.e., from disturbed to more similar to ambient)from the disturbance at the initiation of the experiment.Phylotype number (i.e., band #) was relatively high, andnot significantly different either among treatment types orthrough time (P=0.782 and 0.819, respectively). Again,bacterial compositions in all defaunation treatmentsappeared to be subtly different than ambient sedimentsat t=0 day, and even less similar to one another (e.g., Fig.4B). Whereas little change through time was noted incontrol sediments, bacterial composition in the threedefaunation treatments exhibited temporal shifts, appear-ing to converge toward ambient sediments (Fig. 4B). In allof the frozen and sieved treatments and one (of two) of theanoxic treatments, we found that samples taken att=25 days were more similar to ambient sediment thanthose taken at t=0 day, with each treatment replicateshowing similarity values >88.4% when compared toambient. In all sieved and anoxic replicates, more changein compositionwas observed in the first 24 h, as comparedto the interval between 1 and 25 days. In contrast, in bothreplicates of the frozen treatment, the opposite wasobserved, with greater change from 1 to 25 days thanbetween 0 and 1 day.

4. Discussion

4.1. Macrofaunal numbers

Ourmacrofaunal densities were quite low as comparedto densities found inmany soft-bottom, intertidal habitats.However, densities and biomass are known to vary overorders of magnitude, dependent upon numerous factorsincluding grain size, tidal range, and latitude (Defeo andMcLachlan, 2005). Our abundances are not atypicalrelative to comparable mesotidal, fine/medium sandbeach sediments (e.g., James and Fairweather, 1996;Veloso and Cardoso, 2001). We also note that ournumbers may have been underestimated due to sieve

mesh (1 mm), as it was larger than the mesh size (0.125–0.5 mm) used by many others in such recolonizationstudies (Smith and Brumsickle, 1989; Thrush et al., 1996;Shull, 1997).

The low densities in ambient sediments made itdifficult to rigorously compare the removal ofmacrofaunaamong the different protocols. The defaunation methodsemployed in this study have been used previously (e.g.,freezing by Smith and Brumsickle, 1989; Snelgrove,1994; Shull, 1997; asphyxiation by Thrush et al., 1996;Beukema et al., 1999; sieving by Zajac and Whitlach,1982; James and Fairweather, 1996), although assessmentof removal efficiency seldom has been performed, or wasreported only anecdotally (e.g., Thrush et al., 1996). Inthis study, we utilized the most widely employedprocedures, although specifics of each protocol (e.g.,sieve mesh size, duration of freezing) has varied amongprior studies. In our hands, each of the procedures reducedmacrofaunal numbers, but none with 100% efficiency.Presence of animals in the sieved samples is likely afunction of the efficiency of our 1-mm mesh size (Li,1990; James and Fairweather, 1996), as described above.As the duration of our asphyxiation pre-treatment wasshorter than that of some prior studies (Gamenick et al.,1996; Thrush et al., 1996), it is possible that the treatmentwas insufficient to completely drive the sediment toanoxia. However, based upon the grey and patchy blackappearance of the sediment after removal of the concreteblocks, this is an unlikely explanation for the presence ofmacrofauna in anoxic cores. Based upon the appearanceof some of the macrofauna in the anoxic and frozentreatments, it is also possible that we counted animals thatwere dead, but not completely decomposed, at the time offixation. Smith and Brumsickle (1989) reported that after4 days at field temperatures decayed animals withinfrozen treated sediments were present, but distinguishablefrom macrofauna alive at the time of fixation. As wereplaced and cored the frozen sediment on the same day, itis likely that some fauna killed in the freezing process hadnot yet decomposed. For instance, we observed “naked”hermit crabs in the 0-day samples of the frozen treatment,which were most likely dead at the time of sampling. Thepresence of mobile epifauna (I. obsoleta) in t=0-daytreatment cores suggests that rapid migration prior tosampling was a potential explanation for macrofauna, asthere was a lag of approximately 2 h between placementof the first experimental core and the first core sampling.

The time course for recovery of macrofaunal numbersor biomass in shallow sediments has been shown to varyfrom hours (e.g., Bell and Devlin, 1983) to months(Thrush et al., 1996; Beukema et al., 1999). As this studywas designed to examine disturbance and recolonization


of micro-organisms, the duration of our study was at theshort end of this range. Although there is some hint offaunal recovery in the sieved and anoxic treatments (whiledeclines in the frozen treatmentmay be due to degradationof dead animals), it would appear that the samplingregime was not long enough for clear patterns to emerge.

4.2. Effect on bacterial community

Numerical responses of bacterial assemblages variedamong the three defaunation treatments. The anoxictreatment elicited the most notable response, with a largeinitial increase in active numbers between 0 and 2 days,followed by a decrease until matching ambient numbersby 16 days. An early numerical spike in CTC-stainingcells was also noted in frozen samples, with a relativelyquick recovery by 10 days. Active bacterial densities insieved sediments differed little from ambient sedimentsand tracked ambient numbers closely by 2 days.

Treatment effects on total bacterial numbers weresomewhat less obvious. As the percentage of active cellswas small, ranging from 2 to 23%, patterns observed withactive cells typically would have been swamped bynumbers of dead or dormant bacteria. Moreover, anytreatment effect would need be detectable above the largenumerical increase between 5 and 10 days, which wasobserved in all defaunation treatments, as well as inambient sediments. This spike likely was due to an influxof organic matter, perhaps associated with a benthicmicroalgal bloom, which commonly occurs in this regionin spring (Pinckney and Zingmark, 1993), or with aphytoplankton sedimentation event (Flindt and Nielsen,1992; Noble et al., 2003). The one exception was theanoxic treatment, in which total numbers exceededambient and the other treatments, apparently due to thelarge spike in active cells, which appears to have been aseparate event from the universal increase noted at10 days. A similar pattern was not seen in CTC-stainingcells, perhaps because the peak was missed between the 2-and 10-day samplings, then active cells were replaced bydormant cells. Alternatively, a significant input of organicmatter could have led to a shift to dominance by anaerobicbacterial groups, whichwould not have been detectedwithour CTC staining (Rodriguez et al., 1992). By 10 days,numerical recoverywas largely complete in all treatments,as illustrated by both active and total cell counts, as eachtracked ambient densities closely between 10 and 25 days.

This numerical increase in the anoxic treatment, espe-cially in CTC-staining cells, likely was due to the increasedactivity of aerobic bacteria in response to the re-oxy-genation of the sediment over the first 1–2 days. Sharpspatial redox gradients are common in marine sediments

and are typically associated with elevated bacterial activi-ties and high abundances (e.g., Cavanaugh, 1985;Aller andAller, 1986; Plante and Jumars, 1992). Anoxic sedimentswill be marked by the characteristics of anaerobic degra-dation, i.e., end products of anaerobic respiration such asNH3, H2, H2S, and CH4, incomplete mineralization, andfree fermentation products. Provision of oxygen removesinhibitory end products of anaerobic metabolism and pro-vides a strong oxidant to the functionally aerobic bacteria,thus stimulating bacterial growth and organic matter con-version (Plante et al., 1990). In the present experiment,repeated tidal immersion allowed for a rapid temporal shiftin oxygen levels and redox conditions, resulting in a similarresponse, with a short-lived spike in bacterial densities. Thenumbers of active bacteria most likely decreased over theduration of the experiment due to the reversion of thebacterial community to levels of activity observed in am-bient sediments as they recovered from the initial dis-turbances (Findlay et al., 1990a).

As with the anoxic treatment, frozen sedimentsinitially resembled ambient sediments with respect tobacterial density, showed an early pulse, then tailed off toagain resemble ambient levels. Although numbers ofactive bacteria at t=0 were lowest for this treatment,densities were not significantly lower than ambient. Asmost bacteria can withstand very low temperatures (e.g.,Johnston andBrown, 2002) it is likely thatmost cells werenot killed by the freezing process, but simply entered intoa dormant state and quickly became active again as thesediment thawed, prior to replacement in the field andinitial sampling. Higher organisms, however, would havebeen killed in the freezing process. This pulse in dead (aneasily accessed) organic matter likely explains the earlyincrease in CTC-staining bacteria.

Although the sieved samples did not show significantnumerical differences over time, the higher meansobserved at the initiation of the experiment may be duein part to the change in grain size composition of the sievedsediment. Not only did the sieving treatment removefauna, it also resulted in the removal of shell hash and otherlarge particulates, leading to smaller grain size and greaterhomogeneity. Dale (1974) and others (Hamels et al., 2001)found a highly significant and inverse relationship betweenbacterial numbers and median grain size. Because thereplacement sediment was composed entirely of grains<1 mm in diameter, this may help explain the slightlyhigher counts of active bacteria (normalized tomass) at theinitiation of the experiment. Overall, effects of sievingwere small and recovery was quick, likely via re-establishment of the grain size distribution of surfacesediment, due to waves and the tides, and rapid bacterialrecolonization (Plante and Wilde, 2001).


Initially, the community composition of the anoxic andsieved treatments showed little difference from ambientsediments. Although freezing had the smallest numericaleffects on bacteria, the greatest compositional effects wereobserved in this treatment. Thiswas somewhat of a surpriseas bacteria are known to survive freezing (e.g., long-termstorage of bacterial cultures at −80 °C is a commonpractice). Despite this, numerous studies have demonstrat-ed thatmortality due to freezing can be significant (Restanoet al., 2001; Pesaro et al., 2003), and seasonal temperaturevariation has been implicated in controlling bacterialassemblage structure in marine sediments (King andNedwell, 1984; Upton et al., 1990; Danovaro and Fabiano,1995). More directly, temperature effects on the relativecompetitive abilities of bacteria have been demonstratedexperimentally (e.g., Rutter and Nedwell, 1994), includingstudies employing isolates from estuarine sediments(Oglivie et al., 1997).

The relatively small differences observed in anoxictreatments likely were due to a high proportion of facul-tative anaerobes, for which induced anoxiawould result infunctional, but not necessarily phylogenetic, shifts.Despite reported differential mortality or stimulatory ef-fects associated with mechanical agitation (Findlay et al.,1990a), differences in composition between our sievedambient sediments were slight. However, it is also import-ant to note that although bacteria may be killed duringdefaunation protocols, DNA may remain in the environ-ment and be subsequently extracted and detected viaDGGE. This may have contributed to the disparity bet-ween the numerical and compositional changes observedin the community due to asphyxiation and sieving.

There was a general pattern of compositional“recovery,” or convergence toward ambient sediments,in all three defaunation treatments. However, given thenatural variability of bacterial community structure insediments coupled with the limits of our detectionmethods, it is unclear whether compositional recoverywas complete after 25 days. What does seem to be clearis that all of the treatments lacked the stability of ambientsediments, at least in the initial phases of recovery.

Findlay et al. (1990a) also noted recovery of phospho-lipid fatty acids (PLFA) characteristic of gram-positive andanaerobic prokaryotic groups in sediments, following phy-sical disturbance (i.e., sieving), by between 24 and 48 h.However, other microbial groups, notably aerobic prokar-yotes and sulfate reducers, were still markedly lower orhigher, respectively, after 10 days. Likewise, Langezaalet al. (2003) did not observe re-establishment of pre-treatment PLFA patterns even 49 days after artificial siev-ing disturbance of intertidal sediments. It should be notedthat in both these studies, recovery was monitored in ex-

perimental microcosms and compared to ambient sedi-ments, and it is likely that laboratory incubation itself hadan influence on microbial community structure (Findlayand White, 1983; Findlay et al., 1990a; Langezaal et al.,2003).

In contrast, previous studies have demonstrated rapidrecovery in bacterial assemblages that were subject tobiotic disturbances, e.g., by animal feeding activities(Findlay et al., 1990b; Plante and Wilde, 2001). UsingPLFA analysis, Findlay et al. (1990b) showed recoveryof bacterial metabolic status and community structurewithin 4 h of disturbance associated with the feeding ofenteropneusts and stingrays. Plante and Wilde (2001,2004) employed genomic techniques (DGGE), andsimilarly observed substantial recovery within 2–3 hfollowing gut passage in three diverse deposit feeders.

The time course for recovery in the present study waswithin the broad range observed in the previous studies,and intermediate between those of the abiotic and bioticdisturbances. Some of the important variables affectingrecovery time include the extent and spatial scale of thedisturbance, the degree to which the disturbance impactsphysico-chemical conditions, and the mode of recolo-nization (Plante and Wilde, 2004).

Migration was demonstrated to dominate bacterial re-colonization following deposit feeding (Plante and Wilde,2001, 2004). That immigration dominates following small-scale biotic disturbance means (1) a rapid recovery relativeto other potential recovery modes (i.e., regrowth of sur-vivors of disturbance or recruitment from overlying sea-water), and (2) that the composition of colonizers shouldclosely reflect that of ambient sediments. In larger scaledisturbances, as in the present study, mechanisms of re-colonization are less clear, but the rate of recovery shouldbe slow relative to that of small-scale patches, simply due tothe greater distances that motile bacteria must immigrate.Nonetheless, as the initial disturbance associated with anyof the defaunation treatments used here was fairly minor,recovery of bacterial assemblages that qualitatively andquantitatively resembled those in ambient sediments occursin a period of <10 days for all treatment types. This oc-curred in spite of the physical and chemical disruptions tothe habitat caused by the defaunation procedures. Sievingobliterates the vertical gradients in chemical distributions,while also reducing the median grain size. Although freez-ing likely has smaller physico-chemical effects, metazoanskilled by freezing are retained in the experimental units,thus small patches of organic enrichment in the sedimentsare possible. Although unlikely to induce granulometriceffects, asphyxiation has potentially the greatest chemicalinfluence, especially on oxygen and sulfide levels. Thatbacterial recovery did occur over the time scale of just a few


days, implies a quick re-establishment of pre-treatmentphysico-chemical conditions. The high permeability ofsandy sediments and the prevailing hydrodynamic regimeat our site would have resulted in significant flushing ofporewaters, while periodic emersion would exposeexperimental sediments to even higher levels of oxygenand result in rapid decreases in sulfide levels (Gamenicket al., 1996).

5. Conclusions

Our experimental defaunations had recognizable ef-fects on the bacteria of sediments, with the largest nu-merical effects in the anoxic treatment, and largestcompositional effects via freezing. However, these im-pacts were relatively minor and appeared to be short-lived, as both numerical and genomic recovery was rapid.Relative to recolonization times of benthic macrofauna,typically studied over time scales of weeks to months(e.g., Gamenick et al., 1996; Beukema et al., 1999; Bolamand Fernandes, 2002), these transitory changes insedimentary bacteria are expected to have little effect onanimal recovery. Sieving appears to be the preferreddefaunation method given small numerical and compo-sitional impacts, and rapid overall recovery. However,sieving could lead to granulometric alterations (e.g., grainsize and sorting) that have been shown to influenceinvertebrate larval settling and post-settlement-recruit-ment processes (Koehler et al., 1999; Pinedo et al., 2000).We recommend sieving to defaunate marine sedimentsexcept when sediments are extremely coarse or poorlysorted, or when maintenance of these parameters arecentral to experimental design. If needed, the alternativemethods of driving the sediment to anoxia or freezing canbe employed, albeit with greater initial microbiologicaland chemical deviations from ambient conditions.

Acknowledgements

Primary funding was provided through the NationalScience Foundation grant DEB 0108615. Some of theequipment used for molecular methods was obtainedthrough an NSF equipment grant, DBI-0122336. Addi-tional support was provided to E.T.S. by the College ofCharleston Biology Department's fund for undergrad-uate research. We also thank Thomas Busby and Jere-miah Easley for assistance in the field. [SES]

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