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Spatial Heterogeneity of Bacterial Assemblages in Marine Sediments: The Influence of Deposit Feeding byBalanoglossus aurantiacus .
Estuarine, Coastal and Shelf Science (2002) 55, 97–107 doi:10.1006/ecss.2001.0889, available online at http://www.idealibrary.com on
Spatial Heterogeneity of Bacterial Assemblages in Marine Sediments: The Influence of Deposit Feeding by Balanoglossus aurantiacus. S. B. Wildea and C. J. Plante Department of Biology, Grice Marine Laboratory, University of Charleston, 205 Fort Johnson Road, Charleston, SC 29412, U.S.A. Received 16 October 2000 and accepted in revised form 9 July 2001 Densities and substrate utilization patterns of the bacterial assemblages of three intertidal sandflats were contrasted to investigate spatial heterogeneity. Possible influence of deposit-feeding Balanoglossus aurantiacus (Enteropneusta: Ptychoderidae) was also studied by comparing samples taken from the faecal mounds with surrounding sediments. While there were no significant differences in total bacterial abundance, carbon source utilization patterns, determined using Biolog GN microtitre plates, differed among the sandflats and within the sandflats for samples from grids more than 10 m apart. No consistent quantitative or qualitative differences were detected among clusters of ambient sediment samples taken less than 0·5 m apart. Qualitative differences in microbial assemblages were found between faecal mounds and ambient (>10 cm apart) sediment within a single intertidal flat. These differences were in part due to digestive removal of bacteria, as heterotrophic plate counts and response in Biolog plates (average well colour development, AWCD) were significantly higher for the surrounding sediment. However, when Biolog profiles were normalized to AWCD, it became clear that gut passage resulted in structural shifts in bacterial assemblages. These changes were due to digestion of a subset of ingested bacteria with the concomitant stimulation (or inoculation) of other groups, which were largely unculturable under the conditions employed. These findings illustrate that deposit feeding effects spatial heterogeneity in sedimentary bacterial assemblages. Given the ephemeral nature of these disturbed patches, however, it is not yet clear that deposit feeding is a primary determinant of microbial community structure in this sedimentary landscape. 2002 Elsevier Science Ltd. All rights reserved.
Keywords: bacteria; benthic; spatial distribution; heterogeneity; detritivores; enteropneusta; intertidal sand habitat; South Carolina coast
Introduction Bacteria are vital in ecosystem functions such as nutrient recycling and energy transformation (Blackburn, 1987; Deming & Baross, 1993). Bacterial assemblages in marine sediments have been shown to exhibit spatial heterogeneity in terms of abundance and activity in both the horizontal and vertical dimensions. A vertical profile of sediment reveals high abundance and productivity of microbes in the surface layer, decreasing with sediment depth (e.g. Novitsky, 1983a, b). Vertical changes in microbial community structure are also marked, and are dictated chiefly by redox conditions (Parsons et al., 1984 and refs. within). Horizontally, heterogeneity is less predictable; however, numbers, biomass and activities do vary extensively over both large (see Deming & a Current address: Belle W. Baruch Institute for Marine Biology and Coastal Research, University of South Carolina, Marine Resources Research Institute, P.O. Box 12559, Charleston, SC 29422, U.S.A. E-mail: [email protected]
0272–7714/02/070097+11 $35.00/0
Baross, 1993, for review) and small (e.g. Dale, 1974; Moriarty & Pollard, 1981; Federle et al., 1983) spatial scales. Although rare, studies have demonstrated horizontal differences in composition of microbial assemblages (e.g. based on membrane lipid analyses) over spatial scales from 0·2 cm to 200 m (Federle et al., 1983). Large-scale differences in bacterial abundance and activity likely can be attributed to abiotic factors such as temperature, organic matter (OM) supply and the physical nature of the sediments (grain size, porosity, sorting). Biotic factors are likely to play a role in effecting variability on smaller spatial scales. Deposit-feeding invertebrates might enhance the ‘patchiness’ of a given habitat by altering bacterial assemblages both quantitatively and qualitatively during gut passage. Marine benthic macroinvertebrates have been demonstrated to have profound effects on the sediments in which they dwell (see reviews—Dapples, 2002 Elsevier Science Ltd. All rights reserved.
98 S. B. Wilde and C. J. Plante
1942; McCall & Tevesz, 1982). Deposit feeders have been shown to digest bacteria from sediments with high efficiency (e.g. Dobbs & Guckert, 1988; Plante et al., 1989; Grossmann & Reichardt, 1991). Bacteria that survive passage through the midgut may proliferate within the protected environment of the hindgut and faeces. Using oxygen uptake as a relative index of aerobic bacterial metabolism, it has been shown that benthic detritivore faeces are foci of microbial activity (e.g. Hargrave, 1976; Juniper, 1981). Numerical responses have also been noted, and bacterial growth rates within the hindguts of marine deposit feeders can exceed by orders of magnitude the rates in ambient sediment (Deming & Colwell, 1982; Plante et al., 1989). As a consequence of differential digestion/ regrowth, gut passage alters bacterial community composition relative to that found in surrounding sediments (Dobbs & Guckert, 1988; Plante & Jumars, 1993). Colonization of the faeces via migration is another potential mechanism for stimulating overall microbial activity and biomass on intertidal flats (Plante & Jumars, 1993; Plante & Wilde, 2001). In this two-part study we compared the community structures as demonstrated by bacterial densities and metabolic potentials across various horizontal spatial scales, and included a comparison of deposit-feeder faecal materials vs. surrounding sediments. While the initial study demonstrated the background level of variability among cores taken from centimetres to kilometres apart, the second study examined heterogeneity attributable to gut passage through one common deposit feeder, Balanoglossus aurantiacus. Materials and methods Study sites Sediment samples were collected at Breach Inlet (3246 23 N, 7948 53 W), a protected sandy beach on the north end of Sullivans Island, South Carolina, U.S.A. The intertidal sandflat is situated between a rock jetty to the south and the rocky foundation of a bridge to the north. The dimensions of the flat area are 30 m100 m (Figure 1). The golden acorn worm Balanoglossus aurantiacus (Enteropneusta: Ptychoderidae) is common (0·960·36 m 2), and each animal processes large quantities of sediment due to large body size (up to 1 m in length). Kinbergonuphus jenneri (Polychaeta: Onuphidae) is also common at this site, and is found intermingled with B. aurantiacus. Sandflats on Grice Cove (7·4 km WSW of Breach site; 3245 5 N, 7953 18 W) and Folly River (14·3 km SW of Grice site; 3138 43 N, 7958 12 W), which also contain
N
id Br
ge
Isle of Palms
III II 2 m × 2 m sampling grid
I Jetty
Sullivans Island
0.2 m × 0.2 m clusters 2
0.2 cm core sample
F 1. Sampling design for Breach Inlet to test for spatial heterogeneity among grids, clusters, and samples. Not to scale.
numerous B. aurantiacus (0·830·73 m 2 and 0·250·11 m 2, respectively) were chosen for comparison. Ilyanassa obsoleta (Gastropoda: Nassariidae) was very abundant at the Grice site, but was generally confined to elevations just below those of B. aurantiacus; no other large macroinvertebrates were obvious at the Grice or Folly sites. The median sediment grain sizes of the three beaches were similar (171, 203, and 189 m in diameter for Breach, Grice and Folly, respectively), and all were moderately well sorted (as determined by inclusive graphic standard deviation method; Holme & McIntyre, 1984). Samples were collected during October and November 1997 and water and sand temperature varied less than 2 C among the three sites, while salinity ranged from 29–31 ppt. Percent organic matter (OM) was 0·41, 0·39, and 0·35% at Breach Inlet, Grice Cove and Folly River, respectively. Field collections For the initial study of spatial heterogeneity, samples from Breach Inlet were collected at three spatial scales (Figure 1). During low tide, 3 PVC grids (2 m2 m) were placed randomly (>10 m apart) along a transect 3 m above the waterline and 3 clusters (0·2 m0·2 m) of four samples (0·5 ml core) were collected randomly within each grid. Sediment was collected with a 1 ml syringe with the Luer-end cut off. We refer to comparisons of samples among cores, clusters and grids as centi-, deci- and decametre scales. All samples were transferred to sterile 50 ml
Spatial heterogeneity of intertidal bacterial assemblages 99
centrifuge tubes and held on ice until return to the laboratory (<1 h). Three random samples per grid were collected at the two additional sites (Folly River and Grice Cove). Additional samples collected at Breach Inlet addressed the impact of gut passage through B. aurantiacus on microbial assemblages. Initially, 12 B. aurantiacus faecal mounds were flagged and numbered to mark their locations. Existing faecal mounds were removed to ensure that faecal samples were of the same age. After 1 h, three types of samples, freshly egested faeces, aged faecal mounds (1 h on the sediment) and surrounding sediment, were taken from in and around these mounds. First, a spatula was used to collect 0·2 ml samples of fresh faeces as the worm egested it. Then aged faecal samples were taken by coring the underlying mounds using a 20 ml cut-off syringe. A 0·2 ml sample was retrieved with a sterile spatula from the middle of the cored sample. Finally, adjacent surficial sediment (10 cm from mound centre) was collected with a 1 ml syringe. All samples were transferred to sterile 50 ml centrifuge tubes and held on ice until return to the laboratory (<1 h). Sample preparation Each sample was diluted in 20 ml nine salt solution (NSS) (Westerdahl et al., 1991). In addition, one tube of NSS (20 ml) was employed as a blank. Bacteria were dislodged from the sediment using a short burst (20 s) of sonication with a 3 mm sonic probe (Branson Sonifier 250) at setting 4 on the output control (amplitude=306 m, power output=65 W). Sonication optimization studies demonstrated that the highest average well colour development (AWCD; index of microbial respiration, see below for details) in the Biolog plates occurred with this duration and intensity of sonication. Serial dilutions (10 1, 10 2, 10 3) from these samples were used for Biolog plates, CTC assays, heterotrophic plate counts, and total counts (see below). Samples were then dried to allow expression of bacterial number per dry gram of sediment. Biolog plates. Biolog GN microtitre plates (Biolog Inc., Hayward, CA) are loaded with 95 different carbon sources representing 11 chemical classes (carbohydrates, esters, polymers, carboxylic acids, alcohols, amides, phosphorylated chemicals, amino acids, aromatic chemicals, brominated chemicals, and amines; Garland & Mills, 1991) and a redox dye (tetrazolium violet). Bacterial respiration reduces the tetrazolium dye to formazan within the active cells, so that the pattern of coloured wells (different carbon sources)
represents a metabolic fingerprint of the microbial assemblage. To achieve the optimal dilution for the Biolog inoculations, 20 ml more NSS was added to each sample and vortexed for 30 s at high speed. Biolog plates were then inoculated with 150 l well 1 of the supernate using a multipipettor and incubated aerobically at RT. Colour formation in microplate wells was analysed at t=0, 24, 48, 72, 96 h on a Tritronix Multiskan Plus (Titertek, Huntsville, AL) plate reader at 570 nm. The AWCD for each plate was calculated as the average absorbance of the 95 test wells after subtracting the absorbance of the control well (blank) and setting any negative values equal to 0. CTC reduction assay. When additional samples were collected at Breach Inlet to investigate the impact of deposit feeders on the microbial community, we enumerated metabolically active bacteria. Samples were incubated with redox dye 5-cyano-2,3-ditolyl tetrazolium chloride (CTC; Polysciences, Inc., Warrington, PA) (Rodriguez et al., 1992). Aliquots (2 ml) were taken from the diluted, sonicated sample and transferred to 15 ml centrifuge tubes for the CTC reduction assay. CTC (200 l of 25 mM) was added to each tube and incubated (4 h) at 28 C in the dark while shaking (200 rpm). Duplicate aliquots (1 ml) were retrieved from this incubation and fixed in formalin (4% final concentration) for direct counts of active and total bacteria. Actively respiring cells contained red-staining formazan particles, produced from reduction of colourless CTC, which were visualized with epifluorescence microscopy. Total direct counts. Active and total bacterial counts were performed on samples that had been first incubated with CTC and then stained with DAPI (4,6diamidino-2-phenyl-indole). Direct counts were made with DAPI using an abbreviated version of the protocol of Hymel and Plante (1998). Briefly, samples were centrifuged at 4000g for 15 min then resuspended in Trizma buffer (0·05 M, pH 8·10) and a dispersing agent (Triton100, 0·5%) and sonicated for 20 s with a 3 mm sonic probe at 65 W. Samples were then stained with DAPI (5 l ml 1) for 20 min, recentrifuged to remove stain, and concentrated onto 0·2 m black polycarbonate membrane filters (Poretics, Livermore, CA). Direct counts were made using a Nikon epifluorescence microscope at 1250. DAPIstaining bacteria were counted using a UV filter set (Omega XFO2, 330WB80 exciter, 400EFLP emitter). Active bacteria (CTC staining) were counted using a rhodamine filter set (Omega 605DF55), centre wavelength=605 nm, discriminating filter, full band width at 1/2 maximum transmission=55 nm).
100 S. B. Wilde and C. J. Plante
Due to interference of the CTC with DAPI, total bacteria were taken as the sum of active+DAPI staining cells (Cook & Garland, 1997). For each sample filter set, 20 grids (or more) were counted to include >200 cells per slide. Slide counts from blank tubes containing only sterile NSS were subtracted from both active and total counts. Heterotrophic plate counts. For estimates of colony forming units (CFU) of the Breach Inlet ambient sediments and faecal materials, samples were serially diluted (10 2, 10 3, 10 4), vortexed for 30 s, and plated in duplicate onto marine agar 2216 plates. Colonies were counted after a 96-h incubation at RT.
Statistical analysis One-way ANOVAs were used to test for differences in total bacterial abundance among the three sample sites. Nested ANOVAs were employed to compare among clusters and grids at the Breach site. ANOVA was also used in the second survey at Breach Inlet to compare total bacterial abundance, active bacterial numbers, percent active bacteria, and CFUs among the three sample types: fresh faecal coils, aged faecal coils and ambient sediment. If main effects were significant, Fisher’s LSD correction was used to identify differences between pairs at an of 0·05; if main effects were not significant, the more conservative Bonferroni’s adjustment was used (Milliken & Johnson, 1984). In addition, we investigated more complex spatial patterns of bacterial abundance through the use of spatial autocorrelation. Correlograms of Moran’s I (Cliff & Ord, 1973) vs. inter-sample distance were constructed in a fashion similar to that of Jumars (1978). The autocorrelation index, I, is calculated:
where n is the number of samples, xi is the variate value in sample i, zi =xi x, and
The null hypothesis was that the observed spatial arrangements are the realization of a random permutation of bacterial abundances at various spatial scales. Inter-sample distances were divided into four intervals, corresponding to average distances between cores, cluster, grids and sites. Setting the weighting
factor, wij, equal to 1 for values within an interval, and wij =0 otherwise, produced the plotted values of I. Community level physiological comparisons were conducted looking at three different components: (1) overall metabolic rate; (2) metabolic diversity; and (3) resource utilization patterns (Garland, 1997). To analyse the overall intensity of colour development, AWCD was contrasted among sample types using ANOVA. Richness and evenness of well responses were compared using a substrate diversity index (H ) (Harch et al., 1997; Shannon, 1948) and substrate equitability (J) (Pielou, 1969; Verschuere et al., 1997):
where pi =ratio of corrected OD570 on a carbon source i to the sum of the corrected OD570 on all substrates, and n is the total number of carbon sources and J=H /Hmax where Hmax is the maximal substrate diversity index, obtained with equal intensity of colour development in all 95 wells. Substrate equitability is a rescaling of the substrate diversity such that a J value close to 1 indicates that the bacteria grow in the same proportion on each of the carbon sources, while a value close to 0 indicates that very few carbon sources produce intensive colour. Similarities in carbon source utilization patterns of microbial communities were investigated using multivariate analysis. In order to visualize differences in community respiration patterns among sampling types, we used PCA with the Biolog data (Garland & Mills, 1991, 1994). Additionally, with the first five principal components as variables, we used MANOVA to test for differences among the sample types (Glimm et al., 1997). Since we observed differences in the overall rate of colour development among samples, which can produce variation in the pattern of colour development, we normalized by comparing samples of equivalent AWCD (i.e. all at 0·42 0·01 OD570), but not necessarily the same incubation times. We also tested for spatial autocorrelation in carbon utilization patterns, as described above for abundance, but with the substitution of the first principal components (PC1) for bacterial numbers.
Results Among-site comparison of bacterial densities and metabolic profiles Mean abundance of bacteria in the sediments ranged from 2·11109 cells g 1 at Folly River to 2·94109
Spatial heterogeneity of intertidal bacterial assemblages 101 T 1. Mean (SE) abundance and functional diversity of bacterial assemblages from Breach Inlet, Folly River and Grice Cove sediments Breach
Folly
Grice
Sample information Mean sediment wt (g) No. of replicates
0·120·004b 36
0·160·005a 9
0·140·01b 9
Bacterial abundance Cells109 g 1
2·940·24a
2·110·22a
2·560·30a
Biolog plates (46 h) AWCD (A570) Substrate diversity (H ) Substrate equitability (J)
0·380·04a 4·050·08a 0·890·003a
0·290·09b 3·820·23b 0·840·02b
0·410·06a 4·000·09a 0·880·01a
A change in letter indicates a significantly different mean value for a variable; a>b>c (ANOVA, P<0·05).
2 1 0 PC 2
cells g 1 at Breach Inlet, with no significant differences between sites (Table 1). AWCD in Biolog plates from Grice Cove and Breach Inlet samples were significantly higher than those from Folly Beach after 46 h (P<0·05; Table 1). Substrate diversity values (H ) at Breach Inlet and Grice Cove were also significantly higher than Folly Beach (P<0·05; Table 1). The substrate equitability index was lowest at Folly Beach (P<0·05), while Grice Cove and Breach Inlet values were similar (Table 1). PCA analysis on the original 95 variables revealed differences in the catabolic profiles among the three sites. The separation of samples in PC space can be related to differences in carbon source utilization by examining the correlation of the original variables to PCs. The most important carbon sources in differentiating among the communities were defined as those that had at least half of their variance explained by a principal component. Although no clear patterns emerged with respect to utilization of particular substrate classes, analysis of PC 1 revealed that the Folly assemblage utilized a diverse array of substrates (28 substrates representing 8 of the 11 chemical classes; data not shown) to a lesser degree than those of the Breach or Grice sites (Figure 2). On the basis of PC 2 analysis, Grice was clearly distinct from Breach and Folly, with less utilization of glucuronamide, L-phenyl-alanine, phenylethylamine, and 2,3butanediol, but with greater use of tween 80 (data not shown). Multivariate analysis of variance conducted on the first five principal components (which explained 35% of observed variance) likewise revealed significant differences among sites (P<0·001). All of the two-sample comparisons of the first five PCs were also significant (P<0·001 for each), indicating that all three sites were distinct in terms of the Biolog pattern.
–1 –2 –3
–4
–3
–2
–1 PC 1
0
1
2
F 2. Comparison of catabolic profiles from three sites: Grice Cove, Folly River and Breach Inlet. Plot of first (PC 1) and second (P 2) principal components derived from principal component analyses of the standardized corrected optical density. ( ) Grice Cove; ( ) Folly River; ( ) Breach Inlet.
Spatial heterogeneity at Breach Inlet There were no consistent quantitative differences detected at the spatial scales (decimetre and decametre) sampled at the primary site (Breach Inlet). Bacterial densities at Breach Inlet ranged from 0·90– 6·27109 cells g 1 and were not significantly different among clusters (P=0·24) or among grids (P=0·15). One purpose for employing tests for spatial autocorrelation was to determine whether samples near to one another tended to be more similar, perhaps indicative of unseen environmental gradients. We observed no evidence of significant autocorrelation with respect to abundances at any of the spatial scales examined [Figure 3(a)]. It should be noted, however, that there was a trend toward significance (P=0·10, two-tailed) among cores,
102 S. B. Wilde and C. J. Plante 3
0.3 (a) 0.2
2 + 1
0
–0.0217
–0.1
PC 2
I
0.1
0 –1
–
–0.2 0.1
–2
1 10 100 1000 10 000 Mean inter-sample distance (m)
–3 –4
0.3
–3
–2
–1
(b) 0.2 + 0.1 I
0
1
3
2
PC 1
0
–0.0189
F 4. Comparison of catabolic profiles from three grids within Breach Inlet sandflat; plot of first (PC 1) and second (PC 2) principal components derived from principal component analyses of the standardized corrected optical density. Grid ( ) III; ( ) II; ( ) I.
–0.1 –
–0.2 0.1
T 2. Multivariate analysis of first five PCs* comparing carbon source utilization patterns in microbial communities after 46 h incubation
1 10 100 1000 10 000 Mean inter-sample distance (m)
F 3. Correlogram of Moran’s I versus mean intersample distance for (a) bacterial abundance, and (b) first principal component from Biolog data. Expected values are indicated by dashed line; deviations showing positive or negative autocorrelation are given in the right-hand margin. Solid circles indicate significant autocorrelation; tests of significance were performed according to Cliff and Ord (1973).
among clusters, and among grids. Qualitative differences were detected using Biolog metabolic profiles. Again, no single substrate or substrate class emerged as a clear means to differentiate, but Grid I was clearly separated from Grids II and III (Figure 4), with higher coordinate values for PC 1 and lower PC 2 scores. MANOVA of the first five PCs also demonstrated that Grid I was significantly different from Grid II and Grid III, whereas we found no significant differences among clusters (Table 2). We observed no evidence of significant autocorrelation with respect to PC 1 at small spatial scales; we did, however, see positive spatial correlation at the decametre scale [Figure 3(b)]. Influence of B. aurantiacus Total bacterial abundance was not significantly different for ambient sediment and fresh or 1 h faecal material, but numbers of CTC staining cells were highest in fresh B. aurantiacus faeces (P<0·05 vs. both
Grid All three I vs. II II vs. III I vs. III Among clusters in Grid I† in Grid II§ in Grid III¶
F-criterion
Degrees of freedom
P-value
5·4 5·7 0·9 11·3
10,56 5,18 5,18 5,18
<0·001 0·003 NS <0·001
10,56 5,18 5,18
NS NS NS
5·4 5·7 0·90
*Explains 40% of the observed variability. † Explains 71% of the observed variability. § Explains 67% of the observed variability. ¶ Explains 59% of the observed variability.
aged faeces and sediment). Likewise, the percentage of active bacteria (estimated as CTC cells divided by total cells (CTC+DAPI staining cells) was highest in fresh faeces (P<0·05 vs. sediment, n.s. vs. aged faeces; Table 3). When cultured on marine agar 2216, sediment samples adjacent to the faecal mounds had the greatest mean number of colonies as compared to fresh and aged faecal material (Table 3). Sediment samples consistently showed the most extensive colour development in Biolog plates during our time-course incubation (data not shown). For example, AWCD at 46 h was significantly higher in
Spatial heterogeneity of intertidal bacterial assemblages 103 T 3. Mean (SE) abundance, percent activity and functional diversity of bacterial assemblages from Breach Inlet in fresh faecal coils from B. aurantiacus, aged faecal coils, and adjacent surface sediment. Fresh faecal coils
Aged faecal coils
Sediment
Sample information Mean sediment wt (g) No. of replicates
0·340·02a 12
0·260·01b 12
0·180·01c 12
Bacterial direct counts CTC cells109 g 1 Total bacteria109 g 1 Active bacteria (%)*
2·400·89a 2·640·93a 710·07a
1·210·50b 1·530·53a 590·08a
1·270·21b 2·860·40a 430·03b
Heterotrophic plate counts CFU106 g 1
1·371·24b
0·531·25b
8·116·16a
Biolog plates (46 h) AWCD (A570) Substrate diversity (H ) Substrate equitability (J)
0·300·03b 3·900·07b 0·860·01b
0·270·03b 3·830·07b 0·840·02b
0·420·02a 4·100·02a 0·900·01a
A change in letter indicates a significantly different mean value for a variable; a>b>c (ANOVA, P<0·05). *Mean of values calculated from individual slides.
3 2 1 PC 2
ambient sediment samples than in samples of faecal materials (Table 3). The functional diversity of the microbial community as quantified by substrate diversity and substrate equitability indices was also higher for the ambient sediment samples than for fresh or aged faecal materials (P<0·05 for both; Table 3). PCA of Biolog data showed clear differences between sediment and faecal samples. When 46 hincubated plates were compared, both faecal assemblages gave lower scores for PC 1 and PC 2 than did sediment samples, indicating relatively weaker response in most substrate wells (data not shown), whereas when they were compared at equivalent AWCD (0·420·01; at 46 h incubation for sediment, 96 h for fresh and aged egesta), a different picture emerged (Figure 5). Assemblages associated with sediments exhibited lower relative utilization of tween 80, L-arabinose, xylitol, -ketobutyric acid, -ketoveleric acid, glucuronamide, D-alanine, glycylL-glutamic acid, L-leucine, L-proline, urocanic acid and 2,3-butanediol (data not shown). Individual ANOVAs (with Fisher’s LSD adjustment) generally corroborated these findings in that six of 12 positive correlates for PC 2 showed significantly greater (absolute) well responses by one or both faecal samples as compared to sediments (data not shown; in total, 13 substrates showed a more intense well response in fresh egesta vs. sediment). Amino acids in particular showed higher utilization by bacterial assemblages in fresh egesta, with 17 of 20 showing higher rates
0 –1 –2 –3
–2
–1
0 PC 1
1
2
3
F 5. Comparison of catabolic profiles from Breach Inlet sediment and faecal coils of B. aurantiacus; plot of first (PC 1) and second (PC 2) principal components derived from principal component analyses of AWCD-normalized optical densities. Sample ( ) fresh faecal coils; ( ) aged faecal coils; ( ) sediment.
in egesta (five of these were significantly higher at =0·05, ANOVA), whereas none showed significantly greater response in sediment. In contrast, glucose-6phosphate was utilized to a greater degree by sediment assemblages; a finding also corroborated by ANOVA (not shown). MANOVA using the first five PCs (explaining 50% of variability) likewise revealed significant differences among sample types (P<0·001). Pairwise comparisons demonstrated that the sediment samples differed from the fresh (P<0·001) and aged
104 S. B. Wilde and C. J. Plante
faeces (P<0·001), but the two types of faecal samples were not distinct (P=0·103). Discussion Over the largest spatial scales examined in this study (kilometres), total bacterial numbers were not statistically different. Given that our three sites were similar in those conditions thought to dictate large-scale patterns of bacterial numbers and biomass (see Deming & Baross, 1993, for review), including temperature, OM content of sediments, and gross hydrodynamic regime (evidenced by grain size), these results are not surprising. In contrast, all three sites were shown to be qualitatively distinct. The significant negative autocorrelation for community metabolic potential (i.e. PC 1) was expected, as at the kilometre scale all comparisons are between samples from these disparate assemblages. Clearly, the use of frequently employed quantitative measurements such as total bacterial numbers or biomass, and perhaps also viable/ active cell numbers and activities, can mislead when testing for spatial heterogeneity or changes through time in microbial communities. At finer spatial scales, the Breach Inlet samples showed no significant differences in bacterial densities at the scales of grids or clusters. Qualitative differences, in terms of resource utilization patterns, diversity and equitability, were evident however at intermediate (among grids), but not at finer (among clusters) scales. That a significant positive autocorrelation was observed at the among-grid scale is not as contradictory as might first appear—the MANOVA test at this scale utilized only Breach Inlet samples, whereas the autocorrelation tests employed decametre distances at all three sites. Indeed, PC 1 values at Folly River diverged sharply from the overall mean, and similarities within the Folly samples were largely responsible for the significant correlation. Moran’s I is especially sensitive to extreme values as compared to other indices (e.g. Geary’s c) of spatial autocorrelation (Jumars et al., 1977). These findings are at odds with those of Federle et al. (1983), who more frequently observed significant qualitative differences, based on phospholipid fatty acid (PLFA) analyses of estuarine sediments, at fine (decimetre) as compared to intermediate (decametre) scales. However, too few studies of this type have been done to make generalizations; even within their study, this pattern varied between stations (Federle et al., 1983). One objective of the spatial heterogeneity study was to determine the natural scale of patchiness in bacterial numbers and community composition of the seemingly homogeneous surface sediments at Breach
Inlet. In this manner, we were better able to determine the sampling scheme required to compare bacterial community characteristics of transient biogenic features (in this case, B. aurantiacus faecal coils) to the background sediments. Our findings of no significant decimetre-scale patchiness suggest that our scheme of comparing faecal mounds to nearby (10 cm away) surface sediments was adequate to test for such differences. Again using total bacterial abundance as a quantitative assessment of the microbial community, we were unable to discriminate between samples from the faecal materials of a deposit-feeding invertebrate and those of surrounding sediment. That total numbers of bacteria are not statistically different in faeces and ambient sediments is somewhat surprising as numerous prior studies have demonstrated lower bacterial numbers or biomass in faeces (Lopez & Levinton, 1987; Grossmann & Reichardt, 1991; Hymel & Plante, 2000). Although bacteriolytic activity in guts has been demonstrated for numerous deposit feeders (e.g. Plante & Mayer, 1994; Plante & Shriver, 1998a, b), including hemichordates (Plante & Shriver, 1998b), the potential for growth in hindguts and faeces (Deming & Colwell, 1982; Plante et al., 1989) complicates predictions regarding the fate of ingested microbiota. Moreover, it may be difficult to extrapolate those findings regarding digestion and growth in other deposit-feeding taxa to hemichordates as they produce metabolites (e.g. bromophenols) inhibitory to some bacteria (e.g. King, 1986). Growth inhibition would not be expected, however, since the concentrations of these compounds in faecal casts are extremely low (King, 1986). We propose that, at the time of our sampling, digestion and growth within B. aurantiacus were roughly in balance so that no large net numerical change was observed. Although large positive (growth) and negative effects (digestion) are unlikely to sum to zero, we note that our variances are large (Table 3). In contrast, culturability (either on marine agar 2216 or on Biolog plates) was substantially higher in ambient sediment than in faecal materials. Conversely, there were significantly higher numbers (and percentages) of active cells (as determined by CTC staining) in the fresh faecal materials than in the surrounding sediment. This difference appeared to be short-lived, however, as numbers of active bacteria in aged faeces were similar to those in sediments. The proportional increase in active cells is in accord with the work of Findlay et al. (1990) who observed differences in short-term metabolic status between ambient sediments and the faecal casts of the confamilial enteropneust, Ptychodera bahamensis. Likewise,
Spatial heterogeneity of intertidal bacterial assemblages 105
Duchene et al. (1988), noted increases in the ratio of metabolically active cells, as determined by frequency of dividing cells (FDC) and cell volume, in the posterior guts of deposit-feeding polychaetes. The apparently contradictory results concerning numbers of culturable vs. active cells suggest a shift with gut transit toward a bacterial community proportionally higher in non-culturable types. Some numerically dominant subset of bacteria, which is largely unculturable by the methods employed here, either is stimulated within or inoculated into ingesta, while a portion of culturable heterotrophs are removed. One possible explanation is that the proportion of obligate anaerobes is high in fresh egesta relative to surficial sediments. The PLFA analyses of Findlay et al. (1990) support this argument in that disproportionate increases in sulphate reducers and other anaerobic bacteria were observed in the faecal coils of the hemichordate Ptychodera bahamensis. Proliferation within the gut could result in high numbers of anaerobes, as previous work has shown that the bulk of gut contents of large deposit feeders is anoxic (Plante & Jumars, 1992). Or, our implicit assumption that surficial sediments represent ingested materials may be incorrect, with B. aurantiacus actually ingesting deeper, anoxic sediments. At our study site, at least a fraction (20%, unpubl. data) of fresh B. aurantiacus coils are grey or black in colour, and almost certainly were reducing when ingested. Although the studies of Duncan (1987) suggest that surficial sediments are subducted to depths of 3–10 cm to be ingested by B. aurantiacus, he also demonstrated that these deposit feeders daily shift the positions of their burrows and feeding funnels. Thus, anoxic sediments are likely ingested both when the animal relocates, and to a lesser degree, in normal feeding modes. To clearly distinguish the disturbance effects of translocation vs. predation, this type of study should be conducted on deposit feeders from which foregut samples can be collected and analysed for bacterial numbers or composition (e.g. lugworms; Plante et al., 1989). Another potential explanation for this discrepancy, which is not mutually exclusive of that above, is that the remnant community following gut passage is composed primarily of gram-positive bacteria. Gram-positive bacteria have been demonstrated to resist lysis and survive exposure to digestive fluids of various deposit feeders, while gram-negative bacteria are preferentially lysed (Plante & Shriver, 1998a, b). Researchers working with Biolog plates have noted the difficulty in assaying communities composed of grampositive bacteria (Heuer & Smalla, 1997). Again, the work of Findlay et al. (1990) is supportive in
that their PLFA analyses also indicated selection for gram-positive bacteria with gut passage. The reduction in diversity and equitability, as well as the clear differences in AWCD, in faecal materials vs. sediments support the notion that a significant portion of those bacteria able to metabolize in the aerobically incubated Biolog plates are removed with gut passage. AWCD-normalized metabolic profiles, however, reveal that bacterial assemblages of egesta are compositionally distinct, not merely a subset of the assemblages of surrounding sediments. Previous studies, using a variety of approaches, have also shown compositional shifts in bacterial assemblages with passage through deposit-feeder guts (Dobbs & Guckert, 1988; Duchene et al., 1988; Findlay et al., 1990). Numerous shortcomings of the use of Biolog for microbial community analysis have been noted, and most are related to the fact that the technique is essentially a culture method. Many functional groups are potentially excluded (Haack et al., 1995), either due to inability to utilize the substrates provided or because the incubation conditions (e.g. presence or absence of O2) are inappropriate, while others might increase in relative importance during incubation (Garland 1997; Konopka et al., 1998; Smalla et al., 1998). An additional problem encountered in this study was that of disparate rates of colour development among samples. Such differences (e.g. due to inoculum cell density) can produce variations in the diversity or pattern of colour development that are independent of changes in types of organisms present (Garland, 1997). One approach to remedy this problem is to standardize inoculum density. Although our total bacterial densities did not differ significantly among sample type (albeit, due mainly to large variances), active cell densities and AWCD did differ (Table 3). Almost certainly, AWCD is the more appropriate indicator, as all enumerated cells may not contribute to the Biolog profile. Thus, we compared samples of equivalent AWCD, achieved at disparate incubation times. This method allows for effects caused by differences in inoculum density (i.e. the time it takes to reach a given setpoint in AWCD) and effects due to differences in types of activities of organisms (i.e. multivariate analysis of samples at a given AWCD) to be separately quantified (Garland, 1997; Harch et al., 1997). Despite these potential pitfalls, the method can still be useful to address questions that do not require complete and proportional representation by bacterial groups (Konopka et al., 1998). For instance, simple comparisons of functional diversity or community composition, like those of the present study, can be
106 S. B. Wilde and C. J. Plante
efficiently performed using this method (Garland, 1997; Harch et al., 1997; DiGiovanni et al., 1999). In addition, Biolog can further be used to reveal functional potentials, at least crudely (Sinsabaugh, 1998). Competing methods for community analysis (e.g. PLFA, DGGE) either provide little functional information (PLFA) or require additional, laborious procedures to do so (e.g. genetic fingerprinting). Whether disturbances associated with gut passage significantly impact sedimentary microbial communities will be a function of numerous variables, potentially including the identity of deposit feeders, deposit-feeder densities, feeding rates and the longevity of faecal materials as distinct habitats. If deposit feeders are numerous, and the discrete community of these egesta is persistent, then the entire site (e.g. the Breach Inlet beach site) could be altered with respect to microbial community structure relative to sites absent intense deposit feeding. The present study cannot shed light on this possibility as all three sites included B. aurantiacus populations. Given that any chosen sites are likely to differ in numerous additional abiotic and biotic variables, a comparative approach is unlikely to be useful in this regard; field exclusion experiments would seem to be the most direct way of addressing this question. At less frequent or less severe disturbance, we might expect a patchwork of microcommunities that vary in bacterial numbers and metabolic activities. Such was not detected in this study (e.g. by fine-scale spatial autocorrelation). It should be noted, however, that the relevant spatial scale is not obvious—although individual faecal mounds are on the order of centimetres, B. aurantiacus casting sites are relocated frequently (e.g. the proportion of sites reused is not significantly different from 0% after 1–1·5 d; Duncan, 1987) so that decimetre or metre scale patches of impacted sediment may result. Alternatively, there may be no discernible influence if this type of disturbance is infrequent or the faecal community is quickly invaded. Although all three field sites were chosen for their abundance of B. aurantiacus, our abundances were well below densities found in other locales (e.g. 3–5 greater than our highest densities in Bogue Sound, NC; Duncan, 1987). Perhaps more importantly, compositional (i.e. Biolog profiles) changes appear to be ephemeral. Plante and Wilde (2001) observed that recolonization of egesta from microorganisms in surrounding sediments occurs rapidly, so that differences in community structure were largely erased in 2 h. This spatio-temporal heterogeneity imposed by deposit feeders on a given sedimentary landscape will certainly complicate efforts to predict microbial structure and function. Beyond the types of data presented
here, information regarding the rates and nature of recovery from these biotic disturbances (i.e. modes of recolonization and successional patterns) will be required for patch dynamics models. Acknowledgements This work was funded by National Science Foundation grant OCE 95-04505 made to Craig Plante. Sabrina Hymel and Jennifer Millard contributed valuable technical assistance and advice throughout this study. We thank Peter A. Jumars for suggestions regarding spatial analyses, and 3 anonymous reviewers for suggested improvements on this manuscript. Contribution #191 of the Grice Marine Laboratory, University of Charleston. References Blackburn, T. H. 1987 Microbial food webs in sediments. In Microbes in the Sea (Sleigh, M. A., ed.). John Wiley & Sons, New York, pp. 355–359. Blackburn, T. H. 1988 Benthic mineralization and bacterial production. In Nitrogen Cycling in Coastal Marine Environments (Blackburn, T. H. & Sorensen, J, eds). John Wiley & Sons, Chichester, pp. 171–206. Cliff, A. D. & Ord, J. K. 1973 Spatial Autocorrelation. Pion, London, 178 pp. Cook, K. L. & Garland, J. L. 1997 The relationship between electron transport activity as measured by CTC reduction and CO2 production in mixed microbial communities. Microbial Ecology 34, 237–248. Dale, N. G. 1974 Bacteria in intertidal sediments: Factors related to their distribution. Limnology and Oceanography 19, 509–518. Dapples, E. C. 1942 The effect of macro-organisms upon near shore marine sediments. Journal of Sedimentary Petrology 12, 118–126. Deming, J. D. & Baross, J. A. 1993 The early diagenesis of organic matter: Bacterial activity. In Organic Chemistry (Engel, M. & Macko, S., eds). Plenum Press, New York, pp. 119–144. Deming, J. D. & Colwell, R. R. 1982 Barophilic growth of bacteria from intestinal tracts of deep-sea invertebrates. Microbial Ecology 7, 85–94. Di Giovanni, G. D., Watrud, L. S., Seidler, R. J. & Widmer, F. 1999 Comparison of parental and transgenic alfalfa rhizosphere bacterial communities using Biolog GN metabolic fingerprinting and enterobacterial intergenic consensus sequence-PCR (ERIC-PCR). Microbial Ecology 37, 129–139. Dobbs, F. C. & Guckert, J. B. 1988 Microbial food resources of the macrofaunal-deposit feeder Ptychodera bahamensis (Hemichordata: Enteropneusta). Marine Ecology Progress Series 45, 127–136. Duchene, J. C., Imbaud, P. & Delille, D. 1988 Associated bacterial microflora of a subantarctic polychaete worm Thelepus setosus. Archives of Hydrobiology 112, 221–231. Duncan, P. B. 1987 Burrow structure and burrowing activity of the funnel-feeding enteropneust Balanoglossus aurantiacus in Bogue Sound, North Carolina, USA. P.S.Z.N.I.: Marine Ecology 8, 75–95. Federle, T. W., Hullar, M. A., Livingston, R. J., Meeter, D. A. & White, D. C. 1983 Spatial distribution of biochemical parameters indicating biomass and community composition of microbial assemblies in estuarine mud flat sediments. Applied and Environmental Microbiology 45, 58–63.
Spatial heterogeneity of intertidal bacterial assemblages 107 Findlay, R. H., Trexler, M. & White, D. C. 1990 Response of a microbial community to biotic disturbance. Marine Ecology Progress Series 62, 135–148. Garland, J. L. 1997 Analysis and interpretation of community-level physiological profiles in microbial ecology. FEMS Microbial Ecology 24, 289–300. Garland, J. L. & Mills, A. L. 1991 Classification and characterization of heterotrophic microbial communities on the basis of patterns of community-level-sole-carbon-source-utilization. Applied and Environmental Microbiology 57, 2351–2359. Garland, J. L. & Mills, A. L. 1994 A community-level physiological approach for studying microbial communities. In Beyond the Biomass (Ritz, K., Dighton, J. & Giller, K. E., eds). John Wiley and Sons, Chichester, pp. 77–83. Glimm, E., Heuer, H., Engelen, B., Smalla, K. & Backhaus, H. 1997 Statistical comparisons of community catabolic profiles. Journal of Microbiological Methods 30, 71–80. Grossmann, S. & Reichardt, W. 1991 Impact of Arenicola marina on bacteria in intertidal sediments. Marine Ecology Progress Series 77, 85–93. Haack, S. K., Garchow, H., Klug, M. J. & Forney, L. J. 1995 Analysis of factors affecting the accuracy, reproducibility, and interpretation of microbial community carbon source utilization patterns. Applied and Environmental Microbiology 61, 1458–1468. Harch, B. D., Correll, R. L., Meech, W., Kirkby, C. A. & Pankhurst, C. E. 1997 Using the Gini coefficient with BIOLOG substrate utilization data to provide an alternative quantitative measure for comparing bacterial soil communities. Journal of Microbiological Methods 30, 91–101. Hargrave, B. T. 1976 The central role of invertebrate faeces in sediment decomposition. In The Role of Terrestrial and Aquatic Organisms in Decomposition Processes (Anderson, J. M. & MacFayden, A.,eds). Blackwell, Oxford, pp. 301–321. Heuer, H. & Smalla, K. 1997 Evaluation of communitylevel catabolic profiling using BIOLOG microplates to study microbial community changes in potato phyllosphere. Journal of Microbiological Methods 30, 49–61. Holme, N. A. & McIntyre, A. P. 1984 Methods for Study of Marine Benthos. Blackwell, Oxford. Hymel, S. & Plante, C. 1998 Improved method of bacterial enumeration in sandy and deposit-feeder gut sediments using the fluorescent stain 4,6-diamidino-2-phenyl-indole (DAPI). Marine Ecology Progress Series 173, 299–304. Hymel, S. & Plante, C. 2000 Fate of bacteria transiting the gut of the deposit feeder Abarenicola pacifica: influence of temperature and sediment food concentration. Aquatic Microbial Ecology 22, 93–101. Jumars, P. A., Thistle, D. & Jones, M. L. 1977 Detecting twodimensional spatial structure in biological data. Oecologia 28, 109–123. Jumars, P. A. 1978 Spatial autocorrelation with RUM (Remote Underwater Manipulator): vertical and horizontal structure of a bathyal benthic community. Deep-Sea Research 25, 589–604. Juniper, S. K. 1981 Stimulation of bacterial activity by a deposit feeder in two New Zealand intertidal inlets. Bulletin of Marine Science 31, 691–701. King, G. M. 1986 Inhibition of microbial activity in marine sediments by a bromophenol from a hemichordate. Nature 323, 257–259. Konopka, A., Oliver, L. & Turco, Jr., R. F. 1998 The use of carbon substrate utilization patterns in environmental and ecological microbiology. Microbial Ecology 35, 103–115. Lopez, G. R. & Levinton, J. S. 1987 Ecology of deposit-feeding animals in marine sediments. Quarterly Review of biology 62, 235–260.
McCall, P. L. & Tevesz, M. J. S. 1982 Animal-Sediment Relations. Plenum Press, New York. Milliken, G. A. & Johnson, D. E. 1984 Analysis of Messy Data, Volume I: Designed Experiments. Van Nostrand Reinhold, New York. Moriarty, D. J. & Pollard, P. C. 1981 DNA synthesis as a measure of bacterial productivity in seagrass sediments. Marine Ecology Progress Series 5, 151–156. Novitsky, J. A. 1983a Heterotrophic activity throughout a vertical profile of seawater and sediment in Halifax Harbor, Canada. Applied and Environmental Microbiology 45, 1753–1760. Novitsky, J. A. 1983b Microbial activity at the sediment-water interface in Halifax Harbor, Canada. Applied and Environmental Microbiology 45, 1761–1766. Parsons, T. R., Takahashi, M. & Hargrave, B. 1984 Biological Oceanographic Processes, 3rd edn. Pergamon Press, New York. Pielou, E. C. 1969 An Introduction to Mathematical Ecology. Wiley, New York. Plante, C. J. & Jumars, P. A. 1992 The microbial environment of marine deposit-feeder guts characterized via microelectrodes. Microbial Ecology 23, 257–277. Plante, C. J. & Jumars, P. A. 1993 Immunofluorescence assay for effects on abundance of a naturally occurring pseudomonad during passage through the gut of a marine deposit feeder, Abarenicola pacifica. Microbial Ecology 26, 247–266. Plante, C. J., Jumars, P. A. & Baross, J. A. 1989 Rapid bacterial growth in the hindgut of a marine deposit feeder. Microbial Ecology 18, 29–44. Plante, C. J. & Mayer, L. M. 1994 Distribution and efficiency of bacteriolysis in the gut of Arenicola marina and three additional deposit feeders. Marine Ecology Progress Series 109, 183–194. Plante, C. J. & Shriver, A. G. 1998a Patterns of differential digestion of bacteria in deposit feeders: a test of resource partitioning. Marine Ecology Progress Series 163, 253–258. Plante, C. J. & Shriver, A. G. 1998b Differential lysis of sedimentary bacteria by Arenicola marina: examination of cell wall structure and exopolymeric capsules as correlates. Journal of Experimental Marine Biology and Ecology 229, 35–52. Plante, C. J. & Wilde, S. B. 2001 Bacterial recolonization of deposit-feeder egesta: in situ regrowth or immigration? Limnology and Oceanography 46, 1171–1181. Rodriguez, G. G., Phipps, D., Ishiguro, K. & Ridgway, J. F. 1992 Use of a fluorescent redox probe for direct visualization of actively respiring bacteria. Applied and Environmental Microbiology 58, 1801–1808. Shannon, C. E. 1948 A mathematical theory of communication. Bell System Technical Journal 27, 379–423. Sinsabaugh, R. L. 1998 Functional organization in riverine bacterioplankton: Correlation of extracellular enzyme activity profiles with substrate utilization profiles. Program & Abstracts: Eighth International Symposium on Microbial Ecology p. 303. Smalla, K., Wachtendorf, U., Heuer, J., Liu, W. & Forney, L. 1998 Analysis of BIOLOG GN utilization patterns by microbial communities. Applied and Environmental Microbiology 64, 1220– 1225. Verschuere, L., Dhont, J., Sorgeloos, P. & Verstraete, W. 1997 Monitoring BIOLOG patterns and r/K strategists in the intensive culture of Artemia juveniles. Journal of Applied Microbiology 83, 603–612. Westerdahl, A., Olsson, J. C., Kjelleberg, S. & Conway, P. L. 1991 Isolation and characterization of Turbot (Scophtalmus maximus)associated bacteria with inhibitory effects against Vibrio anguillarum. Applied and Environmental Microbiology 57, 2223– 2228.
Spatial Heterogeneity of Bacterial Assemblages in Marine Sediments: The Influence of Deposit Feeding by Balanoglossus aurantiacus. S. B. Wildea and C. J. Plante Department of Biology, Grice Marine Laboratory, University of Charleston, 205 Fort Johnson Road, Charleston, SC 29412, U.S.A. Received 16 October 2000 and accepted in revised form 9 July 2001 Densities and substrate utilization patterns of the bacterial assemblages of three intertidal sandflats were contrasted to investigate spatial heterogeneity. Possible influence of deposit-feeding Balanoglossus aurantiacus (Enteropneusta: Ptychoderidae) was also studied by comparing samples taken from the faecal mounds with surrounding sediments. While there were no significant differences in total bacterial abundance, carbon source utilization patterns, determined using Biolog GN microtitre plates, differed among the sandflats and within the sandflats for samples from grids more than 10 m apart. No consistent quantitative or qualitative differences were detected among clusters of ambient sediment samples taken less than 0·5 m apart. Qualitative differences in microbial assemblages were found between faecal mounds and ambient (>10 cm apart) sediment within a single intertidal flat. These differences were in part due to digestive removal of bacteria, as heterotrophic plate counts and response in Biolog plates (average well colour development, AWCD) were significantly higher for the surrounding sediment. However, when Biolog profiles were normalized to AWCD, it became clear that gut passage resulted in structural shifts in bacterial assemblages. These changes were due to digestion of a subset of ingested bacteria with the concomitant stimulation (or inoculation) of other groups, which were largely unculturable under the conditions employed. These findings illustrate that deposit feeding effects spatial heterogeneity in sedimentary bacterial assemblages. Given the ephemeral nature of these disturbed patches, however, it is not yet clear that deposit feeding is a primary determinant of microbial community structure in this sedimentary landscape. 2002 Elsevier Science Ltd. All rights reserved.
Keywords: bacteria; benthic; spatial distribution; heterogeneity; detritivores; enteropneusta; intertidal sand habitat; South Carolina coast
Introduction Bacteria are vital in ecosystem functions such as nutrient recycling and energy transformation (Blackburn, 1987; Deming & Baross, 1993). Bacterial assemblages in marine sediments have been shown to exhibit spatial heterogeneity in terms of abundance and activity in both the horizontal and vertical dimensions. A vertical profile of sediment reveals high abundance and productivity of microbes in the surface layer, decreasing with sediment depth (e.g. Novitsky, 1983a, b). Vertical changes in microbial community structure are also marked, and are dictated chiefly by redox conditions (Parsons et al., 1984 and refs. within). Horizontally, heterogeneity is less predictable; however, numbers, biomass and activities do vary extensively over both large (see Deming & a Current address: Belle W. Baruch Institute for Marine Biology and Coastal Research, University of South Carolina, Marine Resources Research Institute, P.O. Box 12559, Charleston, SC 29422, U.S.A. E-mail: [email protected]
0272–7714/02/070097+11 $35.00/0
Baross, 1993, for review) and small (e.g. Dale, 1974; Moriarty & Pollard, 1981; Federle et al., 1983) spatial scales. Although rare, studies have demonstrated horizontal differences in composition of microbial assemblages (e.g. based on membrane lipid analyses) over spatial scales from 0·2 cm to 200 m (Federle et al., 1983). Large-scale differences in bacterial abundance and activity likely can be attributed to abiotic factors such as temperature, organic matter (OM) supply and the physical nature of the sediments (grain size, porosity, sorting). Biotic factors are likely to play a role in effecting variability on smaller spatial scales. Deposit-feeding invertebrates might enhance the ‘patchiness’ of a given habitat by altering bacterial assemblages both quantitatively and qualitatively during gut passage. Marine benthic macroinvertebrates have been demonstrated to have profound effects on the sediments in which they dwell (see reviews—Dapples, 2002 Elsevier Science Ltd. All rights reserved.
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1942; McCall & Tevesz, 1982). Deposit feeders have been shown to digest bacteria from sediments with high efficiency (e.g. Dobbs & Guckert, 1988; Plante et al., 1989; Grossmann & Reichardt, 1991). Bacteria that survive passage through the midgut may proliferate within the protected environment of the hindgut and faeces. Using oxygen uptake as a relative index of aerobic bacterial metabolism, it has been shown that benthic detritivore faeces are foci of microbial activity (e.g. Hargrave, 1976; Juniper, 1981). Numerical responses have also been noted, and bacterial growth rates within the hindguts of marine deposit feeders can exceed by orders of magnitude the rates in ambient sediment (Deming & Colwell, 1982; Plante et al., 1989). As a consequence of differential digestion/ regrowth, gut passage alters bacterial community composition relative to that found in surrounding sediments (Dobbs & Guckert, 1988; Plante & Jumars, 1993). Colonization of the faeces via migration is another potential mechanism for stimulating overall microbial activity and biomass on intertidal flats (Plante & Jumars, 1993; Plante & Wilde, 2001). In this two-part study we compared the community structures as demonstrated by bacterial densities and metabolic potentials across various horizontal spatial scales, and included a comparison of deposit-feeder faecal materials vs. surrounding sediments. While the initial study demonstrated the background level of variability among cores taken from centimetres to kilometres apart, the second study examined heterogeneity attributable to gut passage through one common deposit feeder, Balanoglossus aurantiacus. Materials and methods Study sites Sediment samples were collected at Breach Inlet (3246 23 N, 7948 53 W), a protected sandy beach on the north end of Sullivans Island, South Carolina, U.S.A. The intertidal sandflat is situated between a rock jetty to the south and the rocky foundation of a bridge to the north. The dimensions of the flat area are 30 m100 m (Figure 1). The golden acorn worm Balanoglossus aurantiacus (Enteropneusta: Ptychoderidae) is common (0·960·36 m 2), and each animal processes large quantities of sediment due to large body size (up to 1 m in length). Kinbergonuphus jenneri (Polychaeta: Onuphidae) is also common at this site, and is found intermingled with B. aurantiacus. Sandflats on Grice Cove (7·4 km WSW of Breach site; 3245 5 N, 7953 18 W) and Folly River (14·3 km SW of Grice site; 3138 43 N, 7958 12 W), which also contain
N
id Br
ge
Isle of Palms
III II 2 m × 2 m sampling grid
I Jetty
Sullivans Island
0.2 m × 0.2 m clusters 2
0.2 cm core sample
F 1. Sampling design for Breach Inlet to test for spatial heterogeneity among grids, clusters, and samples. Not to scale.
numerous B. aurantiacus (0·830·73 m 2 and 0·250·11 m 2, respectively) were chosen for comparison. Ilyanassa obsoleta (Gastropoda: Nassariidae) was very abundant at the Grice site, but was generally confined to elevations just below those of B. aurantiacus; no other large macroinvertebrates were obvious at the Grice or Folly sites. The median sediment grain sizes of the three beaches were similar (171, 203, and 189 m in diameter for Breach, Grice and Folly, respectively), and all were moderately well sorted (as determined by inclusive graphic standard deviation method; Holme & McIntyre, 1984). Samples were collected during October and November 1997 and water and sand temperature varied less than 2 C among the three sites, while salinity ranged from 29–31 ppt. Percent organic matter (OM) was 0·41, 0·39, and 0·35% at Breach Inlet, Grice Cove and Folly River, respectively. Field collections For the initial study of spatial heterogeneity, samples from Breach Inlet were collected at three spatial scales (Figure 1). During low tide, 3 PVC grids (2 m2 m) were placed randomly (>10 m apart) along a transect 3 m above the waterline and 3 clusters (0·2 m0·2 m) of four samples (0·5 ml core) were collected randomly within each grid. Sediment was collected with a 1 ml syringe with the Luer-end cut off. We refer to comparisons of samples among cores, clusters and grids as centi-, deci- and decametre scales. All samples were transferred to sterile 50 ml
Spatial heterogeneity of intertidal bacterial assemblages 99
centrifuge tubes and held on ice until return to the laboratory (<1 h). Three random samples per grid were collected at the two additional sites (Folly River and Grice Cove). Additional samples collected at Breach Inlet addressed the impact of gut passage through B. aurantiacus on microbial assemblages. Initially, 12 B. aurantiacus faecal mounds were flagged and numbered to mark their locations. Existing faecal mounds were removed to ensure that faecal samples were of the same age. After 1 h, three types of samples, freshly egested faeces, aged faecal mounds (1 h on the sediment) and surrounding sediment, were taken from in and around these mounds. First, a spatula was used to collect 0·2 ml samples of fresh faeces as the worm egested it. Then aged faecal samples were taken by coring the underlying mounds using a 20 ml cut-off syringe. A 0·2 ml sample was retrieved with a sterile spatula from the middle of the cored sample. Finally, adjacent surficial sediment (10 cm from mound centre) was collected with a 1 ml syringe. All samples were transferred to sterile 50 ml centrifuge tubes and held on ice until return to the laboratory (<1 h). Sample preparation Each sample was diluted in 20 ml nine salt solution (NSS) (Westerdahl et al., 1991). In addition, one tube of NSS (20 ml) was employed as a blank. Bacteria were dislodged from the sediment using a short burst (20 s) of sonication with a 3 mm sonic probe (Branson Sonifier 250) at setting 4 on the output control (amplitude=306 m, power output=65 W). Sonication optimization studies demonstrated that the highest average well colour development (AWCD; index of microbial respiration, see below for details) in the Biolog plates occurred with this duration and intensity of sonication. Serial dilutions (10 1, 10 2, 10 3) from these samples were used for Biolog plates, CTC assays, heterotrophic plate counts, and total counts (see below). Samples were then dried to allow expression of bacterial number per dry gram of sediment. Biolog plates. Biolog GN microtitre plates (Biolog Inc., Hayward, CA) are loaded with 95 different carbon sources representing 11 chemical classes (carbohydrates, esters, polymers, carboxylic acids, alcohols, amides, phosphorylated chemicals, amino acids, aromatic chemicals, brominated chemicals, and amines; Garland & Mills, 1991) and a redox dye (tetrazolium violet). Bacterial respiration reduces the tetrazolium dye to formazan within the active cells, so that the pattern of coloured wells (different carbon sources)
represents a metabolic fingerprint of the microbial assemblage. To achieve the optimal dilution for the Biolog inoculations, 20 ml more NSS was added to each sample and vortexed for 30 s at high speed. Biolog plates were then inoculated with 150 l well 1 of the supernate using a multipipettor and incubated aerobically at RT. Colour formation in microplate wells was analysed at t=0, 24, 48, 72, 96 h on a Tritronix Multiskan Plus (Titertek, Huntsville, AL) plate reader at 570 nm. The AWCD for each plate was calculated as the average absorbance of the 95 test wells after subtracting the absorbance of the control well (blank) and setting any negative values equal to 0. CTC reduction assay. When additional samples were collected at Breach Inlet to investigate the impact of deposit feeders on the microbial community, we enumerated metabolically active bacteria. Samples were incubated with redox dye 5-cyano-2,3-ditolyl tetrazolium chloride (CTC; Polysciences, Inc., Warrington, PA) (Rodriguez et al., 1992). Aliquots (2 ml) were taken from the diluted, sonicated sample and transferred to 15 ml centrifuge tubes for the CTC reduction assay. CTC (200 l of 25 mM) was added to each tube and incubated (4 h) at 28 C in the dark while shaking (200 rpm). Duplicate aliquots (1 ml) were retrieved from this incubation and fixed in formalin (4% final concentration) for direct counts of active and total bacteria. Actively respiring cells contained red-staining formazan particles, produced from reduction of colourless CTC, which were visualized with epifluorescence microscopy. Total direct counts. Active and total bacterial counts were performed on samples that had been first incubated with CTC and then stained with DAPI (4,6diamidino-2-phenyl-indole). Direct counts were made with DAPI using an abbreviated version of the protocol of Hymel and Plante (1998). Briefly, samples were centrifuged at 4000g for 15 min then resuspended in Trizma buffer (0·05 M, pH 8·10) and a dispersing agent (Triton100, 0·5%) and sonicated for 20 s with a 3 mm sonic probe at 65 W. Samples were then stained with DAPI (5 l ml 1) for 20 min, recentrifuged to remove stain, and concentrated onto 0·2 m black polycarbonate membrane filters (Poretics, Livermore, CA). Direct counts were made using a Nikon epifluorescence microscope at 1250. DAPIstaining bacteria were counted using a UV filter set (Omega XFO2, 330WB80 exciter, 400EFLP emitter). Active bacteria (CTC staining) were counted using a rhodamine filter set (Omega 605DF55), centre wavelength=605 nm, discriminating filter, full band width at 1/2 maximum transmission=55 nm).
100 S. B. Wilde and C. J. Plante
Due to interference of the CTC with DAPI, total bacteria were taken as the sum of active+DAPI staining cells (Cook & Garland, 1997). For each sample filter set, 20 grids (or more) were counted to include >200 cells per slide. Slide counts from blank tubes containing only sterile NSS were subtracted from both active and total counts. Heterotrophic plate counts. For estimates of colony forming units (CFU) of the Breach Inlet ambient sediments and faecal materials, samples were serially diluted (10 2, 10 3, 10 4), vortexed for 30 s, and plated in duplicate onto marine agar 2216 plates. Colonies were counted after a 96-h incubation at RT.
Statistical analysis One-way ANOVAs were used to test for differences in total bacterial abundance among the three sample sites. Nested ANOVAs were employed to compare among clusters and grids at the Breach site. ANOVA was also used in the second survey at Breach Inlet to compare total bacterial abundance, active bacterial numbers, percent active bacteria, and CFUs among the three sample types: fresh faecal coils, aged faecal coils and ambient sediment. If main effects were significant, Fisher’s LSD correction was used to identify differences between pairs at an of 0·05; if main effects were not significant, the more conservative Bonferroni’s adjustment was used (Milliken & Johnson, 1984). In addition, we investigated more complex spatial patterns of bacterial abundance through the use of spatial autocorrelation. Correlograms of Moran’s I (Cliff & Ord, 1973) vs. inter-sample distance were constructed in a fashion similar to that of Jumars (1978). The autocorrelation index, I, is calculated:
where n is the number of samples, xi is the variate value in sample i, zi =xi x, and
The null hypothesis was that the observed spatial arrangements are the realization of a random permutation of bacterial abundances at various spatial scales. Inter-sample distances were divided into four intervals, corresponding to average distances between cores, cluster, grids and sites. Setting the weighting
factor, wij, equal to 1 for values within an interval, and wij =0 otherwise, produced the plotted values of I. Community level physiological comparisons were conducted looking at three different components: (1) overall metabolic rate; (2) metabolic diversity; and (3) resource utilization patterns (Garland, 1997). To analyse the overall intensity of colour development, AWCD was contrasted among sample types using ANOVA. Richness and evenness of well responses were compared using a substrate diversity index (H ) (Harch et al., 1997; Shannon, 1948) and substrate equitability (J) (Pielou, 1969; Verschuere et al., 1997):
where pi =ratio of corrected OD570 on a carbon source i to the sum of the corrected OD570 on all substrates, and n is the total number of carbon sources and J=H /Hmax where Hmax is the maximal substrate diversity index, obtained with equal intensity of colour development in all 95 wells. Substrate equitability is a rescaling of the substrate diversity such that a J value close to 1 indicates that the bacteria grow in the same proportion on each of the carbon sources, while a value close to 0 indicates that very few carbon sources produce intensive colour. Similarities in carbon source utilization patterns of microbial communities were investigated using multivariate analysis. In order to visualize differences in community respiration patterns among sampling types, we used PCA with the Biolog data (Garland & Mills, 1991, 1994). Additionally, with the first five principal components as variables, we used MANOVA to test for differences among the sample types (Glimm et al., 1997). Since we observed differences in the overall rate of colour development among samples, which can produce variation in the pattern of colour development, we normalized by comparing samples of equivalent AWCD (i.e. all at 0·42 0·01 OD570), but not necessarily the same incubation times. We also tested for spatial autocorrelation in carbon utilization patterns, as described above for abundance, but with the substitution of the first principal components (PC1) for bacterial numbers.
Results Among-site comparison of bacterial densities and metabolic profiles Mean abundance of bacteria in the sediments ranged from 2·11109 cells g 1 at Folly River to 2·94109
Spatial heterogeneity of intertidal bacterial assemblages 101 T 1. Mean (SE) abundance and functional diversity of bacterial assemblages from Breach Inlet, Folly River and Grice Cove sediments Breach
Folly
Grice
Sample information Mean sediment wt (g) No. of replicates
0·120·004b 36
0·160·005a 9
0·140·01b 9
Bacterial abundance Cells109 g 1
2·940·24a
2·110·22a
2·560·30a
Biolog plates (46 h) AWCD (A570) Substrate diversity (H ) Substrate equitability (J)
0·380·04a 4·050·08a 0·890·003a
0·290·09b 3·820·23b 0·840·02b
0·410·06a 4·000·09a 0·880·01a
A change in letter indicates a significantly different mean value for a variable; a>b>c (ANOVA, P<0·05).
2 1 0 PC 2
cells g 1 at Breach Inlet, with no significant differences between sites (Table 1). AWCD in Biolog plates from Grice Cove and Breach Inlet samples were significantly higher than those from Folly Beach after 46 h (P<0·05; Table 1). Substrate diversity values (H ) at Breach Inlet and Grice Cove were also significantly higher than Folly Beach (P<0·05; Table 1). The substrate equitability index was lowest at Folly Beach (P<0·05), while Grice Cove and Breach Inlet values were similar (Table 1). PCA analysis on the original 95 variables revealed differences in the catabolic profiles among the three sites. The separation of samples in PC space can be related to differences in carbon source utilization by examining the correlation of the original variables to PCs. The most important carbon sources in differentiating among the communities were defined as those that had at least half of their variance explained by a principal component. Although no clear patterns emerged with respect to utilization of particular substrate classes, analysis of PC 1 revealed that the Folly assemblage utilized a diverse array of substrates (28 substrates representing 8 of the 11 chemical classes; data not shown) to a lesser degree than those of the Breach or Grice sites (Figure 2). On the basis of PC 2 analysis, Grice was clearly distinct from Breach and Folly, with less utilization of glucuronamide, L-phenyl-alanine, phenylethylamine, and 2,3butanediol, but with greater use of tween 80 (data not shown). Multivariate analysis of variance conducted on the first five principal components (which explained 35% of observed variance) likewise revealed significant differences among sites (P<0·001). All of the two-sample comparisons of the first five PCs were also significant (P<0·001 for each), indicating that all three sites were distinct in terms of the Biolog pattern.
–1 –2 –3
–4
–3
–2
–1 PC 1
0
1
2
F 2. Comparison of catabolic profiles from three sites: Grice Cove, Folly River and Breach Inlet. Plot of first (PC 1) and second (P 2) principal components derived from principal component analyses of the standardized corrected optical density. ( ) Grice Cove; ( ) Folly River; ( ) Breach Inlet.
Spatial heterogeneity at Breach Inlet There were no consistent quantitative differences detected at the spatial scales (decimetre and decametre) sampled at the primary site (Breach Inlet). Bacterial densities at Breach Inlet ranged from 0·90– 6·27109 cells g 1 and were not significantly different among clusters (P=0·24) or among grids (P=0·15). One purpose for employing tests for spatial autocorrelation was to determine whether samples near to one another tended to be more similar, perhaps indicative of unseen environmental gradients. We observed no evidence of significant autocorrelation with respect to abundances at any of the spatial scales examined [Figure 3(a)]. It should be noted, however, that there was a trend toward significance (P=0·10, two-tailed) among cores,
102 S. B. Wilde and C. J. Plante 3
0.3 (a) 0.2
2 + 1
0
–0.0217
–0.1
PC 2
I
0.1
0 –1
–
–0.2 0.1
–2
1 10 100 1000 10 000 Mean inter-sample distance (m)
–3 –4
0.3
–3
–2
–1
(b) 0.2 + 0.1 I
0
1
3
2
PC 1
0
–0.0189
F 4. Comparison of catabolic profiles from three grids within Breach Inlet sandflat; plot of first (PC 1) and second (PC 2) principal components derived from principal component analyses of the standardized corrected optical density. Grid ( ) III; ( ) II; ( ) I.
–0.1 –
–0.2 0.1
T 2. Multivariate analysis of first five PCs* comparing carbon source utilization patterns in microbial communities after 46 h incubation
1 10 100 1000 10 000 Mean inter-sample distance (m)
F 3. Correlogram of Moran’s I versus mean intersample distance for (a) bacterial abundance, and (b) first principal component from Biolog data. Expected values are indicated by dashed line; deviations showing positive or negative autocorrelation are given in the right-hand margin. Solid circles indicate significant autocorrelation; tests of significance were performed according to Cliff and Ord (1973).
among clusters, and among grids. Qualitative differences were detected using Biolog metabolic profiles. Again, no single substrate or substrate class emerged as a clear means to differentiate, but Grid I was clearly separated from Grids II and III (Figure 4), with higher coordinate values for PC 1 and lower PC 2 scores. MANOVA of the first five PCs also demonstrated that Grid I was significantly different from Grid II and Grid III, whereas we found no significant differences among clusters (Table 2). We observed no evidence of significant autocorrelation with respect to PC 1 at small spatial scales; we did, however, see positive spatial correlation at the decametre scale [Figure 3(b)]. Influence of B. aurantiacus Total bacterial abundance was not significantly different for ambient sediment and fresh or 1 h faecal material, but numbers of CTC staining cells were highest in fresh B. aurantiacus faeces (P<0·05 vs. both
Grid All three I vs. II II vs. III I vs. III Among clusters in Grid I† in Grid II§ in Grid III¶
F-criterion
Degrees of freedom
P-value
5·4 5·7 0·9 11·3
10,56 5,18 5,18 5,18
<0·001 0·003 NS <0·001
10,56 5,18 5,18
NS NS NS
5·4 5·7 0·90
*Explains 40% of the observed variability. † Explains 71% of the observed variability. § Explains 67% of the observed variability. ¶ Explains 59% of the observed variability.
aged faeces and sediment). Likewise, the percentage of active bacteria (estimated as CTC cells divided by total cells (CTC+DAPI staining cells) was highest in fresh faeces (P<0·05 vs. sediment, n.s. vs. aged faeces; Table 3). When cultured on marine agar 2216, sediment samples adjacent to the faecal mounds had the greatest mean number of colonies as compared to fresh and aged faecal material (Table 3). Sediment samples consistently showed the most extensive colour development in Biolog plates during our time-course incubation (data not shown). For example, AWCD at 46 h was significantly higher in
Spatial heterogeneity of intertidal bacterial assemblages 103 T 3. Mean (SE) abundance, percent activity and functional diversity of bacterial assemblages from Breach Inlet in fresh faecal coils from B. aurantiacus, aged faecal coils, and adjacent surface sediment. Fresh faecal coils
Aged faecal coils
Sediment
Sample information Mean sediment wt (g) No. of replicates
0·340·02a 12
0·260·01b 12
0·180·01c 12
Bacterial direct counts CTC cells109 g 1 Total bacteria109 g 1 Active bacteria (%)*
2·400·89a 2·640·93a 710·07a
1·210·50b 1·530·53a 590·08a
1·270·21b 2·860·40a 430·03b
Heterotrophic plate counts CFU106 g 1
1·371·24b
0·531·25b
8·116·16a
Biolog plates (46 h) AWCD (A570) Substrate diversity (H ) Substrate equitability (J)
0·300·03b 3·900·07b 0·860·01b
0·270·03b 3·830·07b 0·840·02b
0·420·02a 4·100·02a 0·900·01a
A change in letter indicates a significantly different mean value for a variable; a>b>c (ANOVA, P<0·05). *Mean of values calculated from individual slides.
3 2 1 PC 2
ambient sediment samples than in samples of faecal materials (Table 3). The functional diversity of the microbial community as quantified by substrate diversity and substrate equitability indices was also higher for the ambient sediment samples than for fresh or aged faecal materials (P<0·05 for both; Table 3). PCA of Biolog data showed clear differences between sediment and faecal samples. When 46 hincubated plates were compared, both faecal assemblages gave lower scores for PC 1 and PC 2 than did sediment samples, indicating relatively weaker response in most substrate wells (data not shown), whereas when they were compared at equivalent AWCD (0·420·01; at 46 h incubation for sediment, 96 h for fresh and aged egesta), a different picture emerged (Figure 5). Assemblages associated with sediments exhibited lower relative utilization of tween 80, L-arabinose, xylitol, -ketobutyric acid, -ketoveleric acid, glucuronamide, D-alanine, glycylL-glutamic acid, L-leucine, L-proline, urocanic acid and 2,3-butanediol (data not shown). Individual ANOVAs (with Fisher’s LSD adjustment) generally corroborated these findings in that six of 12 positive correlates for PC 2 showed significantly greater (absolute) well responses by one or both faecal samples as compared to sediments (data not shown; in total, 13 substrates showed a more intense well response in fresh egesta vs. sediment). Amino acids in particular showed higher utilization by bacterial assemblages in fresh egesta, with 17 of 20 showing higher rates
0 –1 –2 –3
–2
–1
0 PC 1
1
2
3
F 5. Comparison of catabolic profiles from Breach Inlet sediment and faecal coils of B. aurantiacus; plot of first (PC 1) and second (PC 2) principal components derived from principal component analyses of AWCD-normalized optical densities. Sample ( ) fresh faecal coils; ( ) aged faecal coils; ( ) sediment.
in egesta (five of these were significantly higher at =0·05, ANOVA), whereas none showed significantly greater response in sediment. In contrast, glucose-6phosphate was utilized to a greater degree by sediment assemblages; a finding also corroborated by ANOVA (not shown). MANOVA using the first five PCs (explaining 50% of variability) likewise revealed significant differences among sample types (P<0·001). Pairwise comparisons demonstrated that the sediment samples differed from the fresh (P<0·001) and aged
104 S. B. Wilde and C. J. Plante
faeces (P<0·001), but the two types of faecal samples were not distinct (P=0·103). Discussion Over the largest spatial scales examined in this study (kilometres), total bacterial numbers were not statistically different. Given that our three sites were similar in those conditions thought to dictate large-scale patterns of bacterial numbers and biomass (see Deming & Baross, 1993, for review), including temperature, OM content of sediments, and gross hydrodynamic regime (evidenced by grain size), these results are not surprising. In contrast, all three sites were shown to be qualitatively distinct. The significant negative autocorrelation for community metabolic potential (i.e. PC 1) was expected, as at the kilometre scale all comparisons are between samples from these disparate assemblages. Clearly, the use of frequently employed quantitative measurements such as total bacterial numbers or biomass, and perhaps also viable/ active cell numbers and activities, can mislead when testing for spatial heterogeneity or changes through time in microbial communities. At finer spatial scales, the Breach Inlet samples showed no significant differences in bacterial densities at the scales of grids or clusters. Qualitative differences, in terms of resource utilization patterns, diversity and equitability, were evident however at intermediate (among grids), but not at finer (among clusters) scales. That a significant positive autocorrelation was observed at the among-grid scale is not as contradictory as might first appear—the MANOVA test at this scale utilized only Breach Inlet samples, whereas the autocorrelation tests employed decametre distances at all three sites. Indeed, PC 1 values at Folly River diverged sharply from the overall mean, and similarities within the Folly samples were largely responsible for the significant correlation. Moran’s I is especially sensitive to extreme values as compared to other indices (e.g. Geary’s c) of spatial autocorrelation (Jumars et al., 1977). These findings are at odds with those of Federle et al. (1983), who more frequently observed significant qualitative differences, based on phospholipid fatty acid (PLFA) analyses of estuarine sediments, at fine (decimetre) as compared to intermediate (decametre) scales. However, too few studies of this type have been done to make generalizations; even within their study, this pattern varied between stations (Federle et al., 1983). One objective of the spatial heterogeneity study was to determine the natural scale of patchiness in bacterial numbers and community composition of the seemingly homogeneous surface sediments at Breach
Inlet. In this manner, we were better able to determine the sampling scheme required to compare bacterial community characteristics of transient biogenic features (in this case, B. aurantiacus faecal coils) to the background sediments. Our findings of no significant decimetre-scale patchiness suggest that our scheme of comparing faecal mounds to nearby (10 cm away) surface sediments was adequate to test for such differences. Again using total bacterial abundance as a quantitative assessment of the microbial community, we were unable to discriminate between samples from the faecal materials of a deposit-feeding invertebrate and those of surrounding sediment. That total numbers of bacteria are not statistically different in faeces and ambient sediments is somewhat surprising as numerous prior studies have demonstrated lower bacterial numbers or biomass in faeces (Lopez & Levinton, 1987; Grossmann & Reichardt, 1991; Hymel & Plante, 2000). Although bacteriolytic activity in guts has been demonstrated for numerous deposit feeders (e.g. Plante & Mayer, 1994; Plante & Shriver, 1998a, b), including hemichordates (Plante & Shriver, 1998b), the potential for growth in hindguts and faeces (Deming & Colwell, 1982; Plante et al., 1989) complicates predictions regarding the fate of ingested microbiota. Moreover, it may be difficult to extrapolate those findings regarding digestion and growth in other deposit-feeding taxa to hemichordates as they produce metabolites (e.g. bromophenols) inhibitory to some bacteria (e.g. King, 1986). Growth inhibition would not be expected, however, since the concentrations of these compounds in faecal casts are extremely low (King, 1986). We propose that, at the time of our sampling, digestion and growth within B. aurantiacus were roughly in balance so that no large net numerical change was observed. Although large positive (growth) and negative effects (digestion) are unlikely to sum to zero, we note that our variances are large (Table 3). In contrast, culturability (either on marine agar 2216 or on Biolog plates) was substantially higher in ambient sediment than in faecal materials. Conversely, there were significantly higher numbers (and percentages) of active cells (as determined by CTC staining) in the fresh faecal materials than in the surrounding sediment. This difference appeared to be short-lived, however, as numbers of active bacteria in aged faeces were similar to those in sediments. The proportional increase in active cells is in accord with the work of Findlay et al. (1990) who observed differences in short-term metabolic status between ambient sediments and the faecal casts of the confamilial enteropneust, Ptychodera bahamensis. Likewise,
Spatial heterogeneity of intertidal bacterial assemblages 105
Duchene et al. (1988), noted increases in the ratio of metabolically active cells, as determined by frequency of dividing cells (FDC) and cell volume, in the posterior guts of deposit-feeding polychaetes. The apparently contradictory results concerning numbers of culturable vs. active cells suggest a shift with gut transit toward a bacterial community proportionally higher in non-culturable types. Some numerically dominant subset of bacteria, which is largely unculturable by the methods employed here, either is stimulated within or inoculated into ingesta, while a portion of culturable heterotrophs are removed. One possible explanation is that the proportion of obligate anaerobes is high in fresh egesta relative to surficial sediments. The PLFA analyses of Findlay et al. (1990) support this argument in that disproportionate increases in sulphate reducers and other anaerobic bacteria were observed in the faecal coils of the hemichordate Ptychodera bahamensis. Proliferation within the gut could result in high numbers of anaerobes, as previous work has shown that the bulk of gut contents of large deposit feeders is anoxic (Plante & Jumars, 1992). Or, our implicit assumption that surficial sediments represent ingested materials may be incorrect, with B. aurantiacus actually ingesting deeper, anoxic sediments. At our study site, at least a fraction (20%, unpubl. data) of fresh B. aurantiacus coils are grey or black in colour, and almost certainly were reducing when ingested. Although the studies of Duncan (1987) suggest that surficial sediments are subducted to depths of 3–10 cm to be ingested by B. aurantiacus, he also demonstrated that these deposit feeders daily shift the positions of their burrows and feeding funnels. Thus, anoxic sediments are likely ingested both when the animal relocates, and to a lesser degree, in normal feeding modes. To clearly distinguish the disturbance effects of translocation vs. predation, this type of study should be conducted on deposit feeders from which foregut samples can be collected and analysed for bacterial numbers or composition (e.g. lugworms; Plante et al., 1989). Another potential explanation for this discrepancy, which is not mutually exclusive of that above, is that the remnant community following gut passage is composed primarily of gram-positive bacteria. Gram-positive bacteria have been demonstrated to resist lysis and survive exposure to digestive fluids of various deposit feeders, while gram-negative bacteria are preferentially lysed (Plante & Shriver, 1998a, b). Researchers working with Biolog plates have noted the difficulty in assaying communities composed of grampositive bacteria (Heuer & Smalla, 1997). Again, the work of Findlay et al. (1990) is supportive in
that their PLFA analyses also indicated selection for gram-positive bacteria with gut passage. The reduction in diversity and equitability, as well as the clear differences in AWCD, in faecal materials vs. sediments support the notion that a significant portion of those bacteria able to metabolize in the aerobically incubated Biolog plates are removed with gut passage. AWCD-normalized metabolic profiles, however, reveal that bacterial assemblages of egesta are compositionally distinct, not merely a subset of the assemblages of surrounding sediments. Previous studies, using a variety of approaches, have also shown compositional shifts in bacterial assemblages with passage through deposit-feeder guts (Dobbs & Guckert, 1988; Duchene et al., 1988; Findlay et al., 1990). Numerous shortcomings of the use of Biolog for microbial community analysis have been noted, and most are related to the fact that the technique is essentially a culture method. Many functional groups are potentially excluded (Haack et al., 1995), either due to inability to utilize the substrates provided or because the incubation conditions (e.g. presence or absence of O2) are inappropriate, while others might increase in relative importance during incubation (Garland 1997; Konopka et al., 1998; Smalla et al., 1998). An additional problem encountered in this study was that of disparate rates of colour development among samples. Such differences (e.g. due to inoculum cell density) can produce variations in the diversity or pattern of colour development that are independent of changes in types of organisms present (Garland, 1997). One approach to remedy this problem is to standardize inoculum density. Although our total bacterial densities did not differ significantly among sample type (albeit, due mainly to large variances), active cell densities and AWCD did differ (Table 3). Almost certainly, AWCD is the more appropriate indicator, as all enumerated cells may not contribute to the Biolog profile. Thus, we compared samples of equivalent AWCD, achieved at disparate incubation times. This method allows for effects caused by differences in inoculum density (i.e. the time it takes to reach a given setpoint in AWCD) and effects due to differences in types of activities of organisms (i.e. multivariate analysis of samples at a given AWCD) to be separately quantified (Garland, 1997; Harch et al., 1997). Despite these potential pitfalls, the method can still be useful to address questions that do not require complete and proportional representation by bacterial groups (Konopka et al., 1998). For instance, simple comparisons of functional diversity or community composition, like those of the present study, can be
106 S. B. Wilde and C. J. Plante
efficiently performed using this method (Garland, 1997; Harch et al., 1997; DiGiovanni et al., 1999). In addition, Biolog can further be used to reveal functional potentials, at least crudely (Sinsabaugh, 1998). Competing methods for community analysis (e.g. PLFA, DGGE) either provide little functional information (PLFA) or require additional, laborious procedures to do so (e.g. genetic fingerprinting). Whether disturbances associated with gut passage significantly impact sedimentary microbial communities will be a function of numerous variables, potentially including the identity of deposit feeders, deposit-feeder densities, feeding rates and the longevity of faecal materials as distinct habitats. If deposit feeders are numerous, and the discrete community of these egesta is persistent, then the entire site (e.g. the Breach Inlet beach site) could be altered with respect to microbial community structure relative to sites absent intense deposit feeding. The present study cannot shed light on this possibility as all three sites included B. aurantiacus populations. Given that any chosen sites are likely to differ in numerous additional abiotic and biotic variables, a comparative approach is unlikely to be useful in this regard; field exclusion experiments would seem to be the most direct way of addressing this question. At less frequent or less severe disturbance, we might expect a patchwork of microcommunities that vary in bacterial numbers and metabolic activities. Such was not detected in this study (e.g. by fine-scale spatial autocorrelation). It should be noted, however, that the relevant spatial scale is not obvious—although individual faecal mounds are on the order of centimetres, B. aurantiacus casting sites are relocated frequently (e.g. the proportion of sites reused is not significantly different from 0% after 1–1·5 d; Duncan, 1987) so that decimetre or metre scale patches of impacted sediment may result. Alternatively, there may be no discernible influence if this type of disturbance is infrequent or the faecal community is quickly invaded. Although all three field sites were chosen for their abundance of B. aurantiacus, our abundances were well below densities found in other locales (e.g. 3–5 greater than our highest densities in Bogue Sound, NC; Duncan, 1987). Perhaps more importantly, compositional (i.e. Biolog profiles) changes appear to be ephemeral. Plante and Wilde (2001) observed that recolonization of egesta from microorganisms in surrounding sediments occurs rapidly, so that differences in community structure were largely erased in 2 h. This spatio-temporal heterogeneity imposed by deposit feeders on a given sedimentary landscape will certainly complicate efforts to predict microbial structure and function. Beyond the types of data presented
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