1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Literature Cited

A before-after-control-impact (BACI) experiment was conducted to examine the effects of hydraulic clam dredging on sediment biogeochemistry of a leased shellfish bed of Mercenaria mercenaria, northern quahog, over the course of an entire growing season. Six study plots (0.67 ha each), three dredged and three not dredged, off of Milford, Connecticut, in Long Island Sound, were sampled from May to October 2009 for porewater fluxes of total ammonia, oxygen, and hydrogen. Particulate samples were also analyzed for grain size, total nitrogen, total carbon, total sulfur, and organic carbon. Statistical analysis indicated no significant difference between dredged and not dredged sites. Grain size and oxygen flux explained 22% of the variation in the total benthic species assemblages; grain size and either total carbon or organic nitrogen explained 18% of the variation in molluscan abundance. Our study demonstrates that one-time hydraulic shellfish harvesting had minor effects on the sediment chemistry of a leased clam bed.

With increased shortages from capture fisheries and a growing human population, aquaculture has become one of the fastest growing, food-producing sectors in the world (FAO 2010). Annual aquaculture production, which represented less than 1 million m.t. in 1950, has risen at an annual growth rate of 8.3% and reached 52.5 million m.t. by 2008 (FAO 2010). Although bivalve aquaculture currently represents only 25% of the world's aquaculture production (FAO 2010), over 80% of the shellfish that are consumed are obtained through aquaculture practices, which have led to high scrutiny concerning potential effects of bivalve aquaculture on the environment (Shumway 2011). Shellfish farming practices can vary widely depending on a variety of factors including species, tradition, environmental conditions, social acceptance, and local regulations (Ferreira et al. 2011).

Molluscs have long been harvested from estuaries by native people and colonial settlers for hundreds of years (MacKenzie et al. 2002a, 2002b). Historically, the states of Florida, Virginia, and Connecticut are the highest producers of molluscan shellfish (MacKenzie et al. 2002b), with Crassostrea virginica (the eastern oyster) and Mercenaria mercenaria (northern quahog) the two most frequently harvested species. Increased disease occurrence (i.e., Dermo), loss of habitat, and other environmental stressors have resulted in a decline in harvests of C. virginica since the 19th century (Mackenzie 1996). This reduction in oyster production contributed to increased commercial harvest of northern quahog during the 1920s, which became a promising commercial enterprise, following the introduction of the hydraulic dredge (1958 in Connecticut) and seed hatcheries in the 1960s (Mackenzie et al. 2002b). As the dominant producer of northern quahog, the USA harvested over 4.1 million m.t. during 2011, valued at US$87 million (

As the aquaculture industry continues to grow, there is an increased need to ensure that the cultivation and harvest of northern quahog have minimal negative effects on the environment. Hard clam aquaculture may interact with the ecosystem through (1) food consumption and waste production and (2) harvesting and bed maintenance (Dumbauld et al. 2009). In Long Island Sound in Connecticut, the seafloor is surveyed and leased to harvesters, who rely on natural recruitment of hard clams. All the available shellfish beds in the state (28,328 ha) are currently under lease with income from production rising from US$3.5 million in 1990 (146,250 bags) to US$17.4 million (425,294 bags) by 2010 (, Connecticut Department of Agriculture). In the adjacent New York waters of Long Island Sound, clams are harvested either from open grounds or, in some cases, young hatchery-reared clams are seeded to populate leased beds for eventual harvest.

In Connecticut, towed hydraulic dredges are used to harvest hard clams. These dredges use high-pressure water jets to loosen the sediments and dislodged clams are collected in mesh bags as the dredge bar passes over the fluidized bottom (MacKenzie et al. 2002a). Water pressure is sufficient to remove clams without shell damage (Jolley 1972). Because hard clams grow slowly, cultivated shellfish beds are dredged every 3–5 years to allow clams to reach harvestable sizes (MacKenzie et al. 2002a, 2002b). The use of towed fishing gear elicits some concerns because of potential damage to non-target benthic organisms, chronic effects to diversity in the dredge track, and potential biogeochemical changes in the sediments (Levy 1998; Watling and Norse 1998; Watling 2005). The effects of dredging on leased beds are considered less extensive than those on wild beds because clammers know when to harvest in order to maximize the catch of market size northern quahog, thereby reducing tow length and mortality of nontarget organisms (Stokesbury et al. 2011). Sediment type, dredging gear, depth of water column, currents, tides, and time of year are among the factors that influence dredging outcomes (Falcão et al. 2003). Potential effects to the benthic environment can include changes in the biological community (Mercaldo-Allen and Goldberg 2011; Goldberg et al. 2012) and in the biogeochemistry of the sediments (Mayer et al. 1991; Falcão et al. 2003). Some possible biogeochemical changes include resuspension of ammonia from sediment porewater (Fanning et al. 1982), changes in redox potential (Aller 1980; Ingall and Jahnke 1994), changes in sediment grain size and porosity (Lenzi et al. 2005), changes in sediment particulate carbon/nitrogen (Lenzi et al. 2005), and release of anoxic sediments to the surface (Badino et al. 2004). The effects on the benthic community can vary from one location to another depending on the dredging gear being used and on the physical, chemical, and biological components of the local environment (Stokesbury et al. 2011).

Although the practice of hydraulic dredging for hard clam harvest has been conducted in Connecticut since the 1960s, information concerning biogeochemical effects and effects to the benthic community from dredging on leased beds is limited. Before-after-control-impact (BACI) studies are frequently used to distinguish naturally occurring environmental changes from manmade activities (Underwood 1994; Dame et al. 2000, 2002; Hewitt et al. 2001; Stokesbury et al. 2011). In a BACI design, the control and impact areas are assumed to behave similarly except for any harvest-caused disturbances (Green 1979). Marine environments can be highly variable on small spatial scales; therefore, statistics that can address complex inequalities are utilized (Black and Miller 1991, 1994; Underwood 1991, 1992, 1994; Rangeley 1994). Assuming the null hypothesis, that there are no differences between the control (non-dredged) and impact (dredged) site, the experimental protocol involves sampling preimpact, immediately postimpact, and continued sampling during the recovery phase (Stokesbury et al. 2011).

We designed a BACI study to assess the biochemical effects of hydraulic dredging on a historically cultivated clam bed in Long Island Sound. We measured sediment grain size, porewater fluxes (total ammonia, hydrogen, and oxygen flux), sedimentary total carbon, nitrogen, sulfur, and organic carbon to compare the biogeochemistry of the sediments between dredged and not dredged sites and before and after dredging.

Materials and Methods

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Literature Cited

The commercial clam bed was located in Long Island Sound at 41°11′N, 73°5′W offshore of Milford, Connecticut, USA (Fig. 1). A commercial clammer provided us with 4 ha on his leased bed, where northern quahogs were last harvested in 2007, to conduct the BACI experiment. According to nautical charts, this area was expected to have fairly uniform grain size with a tidal cycle water depth varying from 4.9 to 6.1 m. The 4 ha plot was divided into six, 0.67 ha boxes, which consisted of three control areas (1, 3, 5) and three impacted plots (2, 4, 6). To facilitate spatial randomization, each plot was further subdivided into nine boxes, and on each collection date, one box was randomly selected for sampling.


Figure 1. Study site in Long Island Sound (inset) off the coast of Milford, Connecticut, USA. Projection shows a schematic of the six experimental plots (82 × 122 m each), indicating dredged (D) and not dredged (ND) plots. Depths at mean low water are indicated in feet (1 ft = 0.31 m) “hrd S” = hard sand, “sft S” = soft sand. The numbers in the brackets are the mean surface (0–2 cm) grain size with standard error. Each letter represents a different homogenous group.

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The BACI design requires preimpact, postimpact, and recovery sampling. Beginning on May 28, 2009, samples were taken on both control and impacted sites on a biweekly schedule aboard the NOAA Fisheries R/V “Victor Loosanoff.” One-time dredging of the “impacted” sites was conducted by the Jesse D. Shellfish Company on July 6, 2009, using a hydraulic clam dredge weighing 204 kg at a towing speed of 1.2–1.6 knots. This dredging methodology is typical of harvesting practices conducted on leased commercial beds. A total of 10 sampling trips were completed over a 24-wk time period.

Sediment Sampling

Sediment cores were obtained randomly from different locations in the study area (Fig. 1) using the sediment corer described in Alix et al. (2013). The coring device used was a gravity surface corer that allowed for the recovery of the sediment–water interface and the sediment immediately below, with no disturbance to the bottom (Hongve 1972). At each station, two sediment cores were collected for analysis of porewater pH, total ammonia, and oxygen concentrations.

Fine resolution sediment core profiling (1 mm) yields better flux calculations and resolution than sectioning; however, the technology to accomplish fine resolution sampling was not always available. An oxygen micro-optical, 140-µm probe in a needle (Loligo Systems, Tjele, Denmark1) was used for oxygen profiling. The probe was attached to a micro-manipulator for millimeter-scale resolution of oxygen profiles. An MI-414 pH electrode in a 16-gauge needle was attached to the micro-manipulator to obtain millimeter-scale resolution for pH. Oxygen and pH measurements were determined in 1 mm increments in the top 10 mm of each core. As microelectrode probes for total ammonia were not available, we obtained porewater from cores that were sectioned at 2-cm intervals. Each section was placed in a 50-mL centrifuge tube and tubes were centrifuged at 1000 g for 20 min. The porewater was decanted, filtered through a 0.45-µm filter, and the effluent was collected in a 15-mL centrifuge tube placed immediately on ice in the dark, for determination of subsequent total ammonia. The sediment remaining in the centrifuge tube was analyzed for particulate nitrogen, carbon, and sulfur.

Total ammonia was determined within 24 h of sample collection using a QuAAtro autoanalyzer (Seal Analytical, Mequon, WI, USA) using the Berthelot reaction, as described by Hansen and Koroleff (1999). The detection limit of the instrument was 0.05 μM.

Particulate carbon, nitrogen, and sulfur were determined with a Costech ECS 4010 CHNS elemental analyzer (Valencia, CA, USA). All samples were dried in an oven (60 C) overnight. Sediments were ground using a Retsch PM 200 grinder (Newton, PA, USA) to a size of 63 µm. Approximately 3-µg subsamples of sediment were weighed into tin boats with 0.5 µg of vanadium oxide added for the determination of total carbon, nitrogen, and sulfur. A subsample of each sediment section was also acidified for the determination of organic carbon using the same elemental analyzer. A standard reference material (SRM 8704 Buffalo River Sediment) was analyzed with the samples, with a reported total carbon value of 3.351%. Recovery of total carbon measured 3.150 ± 0.327% (n = 50), within the reported value range.

Flux Calculations

Based on the oxygen micro-profiles, it appears that bioturbation effects in the sediments were minor. As no oxygen could be detected beyond 1 cm, sediment ammonia, hydrogen, and oxygen fluxes were calculated using Fick's First Law of diffusion (Berner 1980). This method is commonly used for shallow-water, estuarine sediments (Emerson et al. 1984, Hammond et al. 1985) where molecular diffusion represents the major component during exchange of dissolved substances between bottom sediments and overlying water and is expressed by the formula:

  • display math

where J is the flux, ϕ is the porosity, m has a value of 3 for these surface sediments (Ullman and Aller 1982), Ds is the effective diffusion coefficient, and inline image is the observed concentration gradient of porewater. Molecular diffusion coefficients in seawater were corrected for the in situ, bottom-water temperature. Positive numbers indicate a net flux into the sediment while negative numbers indicate a net flux out of the sediments.

Data Analysis and Statistics

A standard BACI-style statistical analysis of main effects and interactions was performed using the permutational multivariate analysis of variance (PERMANOVA) add-on to the statistical software Primer v6 (Anderson et al. 2008; Clarke and Gorley 2006). PERMANOVA has the advantage of no assumptions of normality and tests all main effects and interactions from the BACI style of experimental design. PERMANOVA was used to determine the main effects of treatment (impact versus control), time period (predredging versus postdredging), sample date (nested in time period), and plot (nested in treatment). This analysis was completed for all measured chemical parameters. A draftsman plot was examined prior to analysis to ensure that values for each variable were evenly distributed, that is, not heavily skewed or containing extreme outliers.

Benthic assemblage data from the same samples are described thoroughly in Goldberg et al. (2012). The species composition data from Goldberg et al. (2012) were used in a distance-based redundancy analysis to investigate the relationship between sediment chemistry and benthic assemblages. The analysis was performed using the DISTLM routine within the PERMANOVA program (McArdle and Anderson 2001; Anderson et al. 2008). Benthic-assemblage data were square-root transformed and the Bray–Curtis resemblance measure was used to generate similarity matrices for the total benthic assemblage and for the subset of the assemblage belonging to the phylum Mollusca. As most of the Connecticut shellfish industry relies on natural set, we were interested in identifying the relationships between the abundance of molluscs and our measured physical and chemical parameters. Ratios of total and organic carbon to nitrogen were not included among the predictor variables. A draftsman plot was used to check for multi-colinearity among the remaining chemical variables, and because all correlations were well below the recommended cutoff of 0.95, these variables were included in the DISTLM routine as predictor variables. The “Best” selection procedure was used for model-building, which examined all possible combinations of predictor variables. Both AICc and BIC were used as selection criteria, and models that had AICc or BIC values within 2 units of the best model are included here (Schwartz 1978; Sugiura, 1978; Anderson et al. 2008).


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Literature Cited

Table 1 reports the results of the BACI-style statistical analysis of the data. Significant main effects of sampling date and plot were observed in several of the chemical parameters. No main effects of dredging were detected. Short-term effects of dredging were observed for organic nitrogen and hydrogen flux (detailed below), but these differences disappeared within weeks of the dredging event.

Table 1. Results of BACI-style statistical analysis. Main effects include treatment (control versus impact), sampling performed pre dredging versus postdredging, sample date, and plot.a
Factor (df)Mean grain sizeOxygen fluxAmmonia fluxHydrogen fluxOrganic nitrogenOrganic carbonTotal nitrogenTotal carbonTotal sulfur
  1. AICc = Modified Akaike Information Criterion; BIC = Bayesian Information Criterion; BACI = before-after-control-impact; MS = mean squares; RSS = residual sum of squares.

  2. a

    Interactions of main effects are also included. Degrees of freedom for each test are inside the parentheses. Significant differences (P < 0.05) are indicated in bold.

Treatment (1)
P0.520.66  0.210.460.300.670.200.630.59
F0.440.20  1.850.641.220.191.980.240.32
Predredging versus postdredging (1)
P0.120.78  0.560.550.120.100.600.220.55
MS0.43<0.01  35.170.430.6523.44 0.0517.16 0.15
F3.660.08  0.390.434.145.240.332.040.41
Sample date (8)
P0.10<0.01  0.04<0.01
MS1.031.23  632.94  1.400.
F0.4411.60  2.417.393.312.182.101.651.56
Plot (4)
P<0.01<0.01  0.920.060.730.010.63<0.01  0.08
MS1.440.95 60.650.500.017.600.3123.48 0.93
F14.598.96  0.232.640.503.880.664.352.38
Predredging versus postdredging × treatment (1)
P0.180.11  0.260.340.500.810.380.150.70
MS0.050.44 163.14 0.46 0.0751.390.499.060.27
F1.752.32  1.431.210.860.501.111.930.62
Predredging versus postdredging × plot (4)
P0.780.72  0.730.930.030.890.310.810.15
F0.430.54  0.510.
Sample date × treatment (8)
P0.890.14  0.750.
F0.431.70  0.632.611.453.140.601.000.91

Grain size varied consistently among the plots, with fine sand located near shore, becoming very fine sand moving offshore (Fig. 1). There was no significant effect of grain size on any of the chemical parameters measured (Table 1). There was concern that grain size differences could be masking minor, but significant, effects of dredging because there were differences in grain size among the plots. Thus, the PERMANOVA analysis was performed first using grain size as a covariate and then also using organic carbon as a covariate. In general, running PERMANOVA with grain size as a covariate eliminated significant plot effects that were observed for several of the chemical parameters, but in no instance did it alter the results of the test of treatment (i.e., dredged versus not dredged). Running organic carbon as a covariate had no effect on the results of the PERMANOVA analysis.

The oxygen flux varied from a mean of 210 mmol/m2/d to 1104 mmol/m2/d at the control site, with a similar range observed at the impact site (Fig. 2). For both the control and impact sites, and throughout the sampling season, oxygen was fluxing into the sediments. Significant effects of sampling date were detected (P < 0.01). From May through August, the oxygen flux increased with the highest concentration occurring in August, and values decreasing after. No significant differences were observed between the control and impact sites (P = 0.66), predredged versus postdredged samples (P = 0.78), nor any of the interaction terms (all P > 0.11, Table 1).


Figure 2. Diffusive calculated porewater fluxes for each of the sampling dates for oxygen, total ammonia, hydrogen ion, and sedimentary organic carbon, total carbon, nitrogen, and sulfur. The arrow indicates when dredging occurred on the time line.

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Total ammonia flux varied from −21.51 mmol/m2/d to −65.90 mmol/m2/d at all sites (Fig. 2). Significant effects of sampling date were detected (P = 0.04). Total ammonia fluxed out of the sediments during the sampling period with the largest fluxes observed during the month of August. There was no significant difference between the control and impact sites (P = 0.21), predredged versus post dredged samples (P = 0.56), or any of the interaction terms (all P > 0.26, Table 1).

Unlike the flux from total ammonia and oxygen, which was consistently unidirectional throughout the season, the hydrogen flux was more variable, ranging from negative −0.52 mmol/m2/d to 0.58 mmol/m2/d (Fig. 2). A significant interaction was observed between sampling date and treatment (P = 0.04). Significant differences between control and impact sites were observed on sampling dates May 18, 2009 (P = 0.01), and July 7, 2009 (P = 0.03). For both these sampling dates, the control had a lower flux of hydrogen than the impact sites. On May 18, the control site had a hydrogen flux of −0.39 ± 0.27 mmol/m2/d, while the impact site had a flux of −1.06 ± 0.65 mmol/m2/d. On July 7, a day after dredging, a hydrogen flux of + 0.02 ± 0.13 mmol/m2/d was measured at the control site while the impact site had a flux of +0.29 ± 0.08 mmol/m2/d. There was no significant difference between predredged and postdredged samples (P = 0.55), or for the interaction between predredged and postdredged samples with plot (P = 0.93).

Particulate organic carbon ranged from 2.10 to 6.61 mg/g for the control sites, while the impact sites ranged from 2.56 to 6.12 mg/g (Fig. 2). A significant interaction was observed between sampling date and treatment (P = 0.01). Significant differences between control and impact sites were observed on July 7, 2009 (P = 0.02), and August 4, 2009 (P < 0.01). These observed differences between control and impact sites were not consistent in direction; control sites had a lower mean particulate carbon on July 7 (4.07 ± 0.78 and 6.12 ± 0.78 mg/g, respectively), but impact sites had a lower mean particulate carbon on August 4 (2.56 ± 0.97 and 5.52 ± 0.24 mg/g, respectively). No significant differences were observed related to dredging treatment (P = 0.67) or predredged versus postdredged sampling (P = 0.10).

The total carbon concentration varied from 5.00 to 12.47 mg/g for both the control and impact sites with no significant treatment effect (P = 0.63, Fig. 2). No significant differences were observed for total carbon between predredged and postdredged samples (P = 0.22) sampling date (P = 0.15), or any of the interaction terms (all P > 0.15, Table 1).

Total nitrogen varied from 0.54 to 2.10 mg/g across all samples with no significant treatment effect observed (P = 0.20, Fig. 2). As with total carbon, there was also no observed significant differences between predredged versus postdredged samples (P = 0.60) sampling date (P = 0.06), or any of the interaction terms (all P > 0.31, Table 1).

Total sulfur content varied from 0.45 to 5.69 mg/g across all sites and dates (Fig. 2), with no significant differences observed between control and impact sites (P = 0.59), between predredged and postdredged samples (P = 0.55), sampling date (P = 0.18), or any of the interaction terms (all P > 0.15, Table 1).

Benthic invertebrate species composition data were reported previously (Goldberg et al. 2012). Some of the dominant species included amphipods Ampelisca spp., Calliopius laeviusculus and Leptocheirus pinguis; polychaetes Glycera spp., Clymenella torquata and Nephtys spp.; crustaceans Pagurus longicarpus, Pinnixa spp., and Crangon septemspinosa; and bivalves M. mercenaria and Yoldia limatula (Goldberg et al. 2012). Distance-based redundancy analysis, a form of multivariate multiple regression, was used to partition the variance observed in the biological assemblages using the multivariate matrix of chemical data (McArdle and Anderson 2001; Anderson et al. 2008). Marginal tests for grain size and oxygen yielded significant P-values (<0.001) for the total benthic assemblage. Marginal tests for oxygen flux and ammonia flux yielded significant P-values (<0.001 and 0.03, respectively) for the assemblage of molluscs alone. Both the Akaike and Bayesian model indicated that grain size and oxygen flux were the best predictors of community composition, but these two factors explained just 22% of the observed variance (Table 2). The addition of organic nitrogen, hydrogen flux, organic carbon, or total nitrogen to the model improved the explanatory power by an additional 2–4%. The multiple regression analysis was also performed with the mollusc assemblages. Grain size was again the best predictor of mollusc assemblage, explaining 14% of the variation in abundance, and the addition of either total carbon or organic nitrogen increased the predictive ability to 18% (Table 3).

Table 2. Model results for chemical parameters as predictors of benthic assemblage species composition
30.54335.450.2252,648Grain size, oxygen flux
330.56336.90.2649,989Grain size, oxygen flux, organic nitrogen
331.16337.50.2550,651Grain size, oxygen flux, hydrogen flux
331.20337.540.2450,696Grain size, oxygen flux, organic carbon
331.37337.710.2450,883Grain size, oxygen flux, total nitrogen
Table 3. Model results for chemical parameters as predictors of molluscan assemblages
323.50326.880.1447,491Grain size
323.91328.820.1845,580Grain size, total carbon
323.97328.880.1845,641Grain size, organic nitrogen


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Literature Cited

The chemical effects of harvest dredging on sediment chemistry are highly specific to local habitat, environment, and the level of physical impact. Disruption of sediments during harvest can potentially release porewater and free sequestered nutrients (Coen 1995), resulting in short-term oscillations in chemistry at the sediment surface. We found that the one-time dredging event on July 7, 2009, on a shellfish bed in Long Island Sound did not have a significant, lasting effect on any of the chemical parameters that we measured (Table 1). There was an interaction between sampling date and treatment for the hydrogen ion flux and particulate organic carbon (Table 1), but this was short lived and dissipated within the next one or two sampling intervals.

Nearshore coastal sediments, prone to frequent natural disruption, are likely to recover chemical equilibrium rapidly following brief, pulse disturbance events. In these environments, the effects of shellfish dredging on bottom sediments may be indistinguishable from naturally occurring changes to the seabed (Constantino et al. 2009; Sciberras et al. 2013). Falcão et al. (2003) found an immediate drop in porewater chemical parameters including ammonium, nitrates, organic nitrogen, phosphate, and silicate just after clam dredging in Portugal, but these values returned to original values within minutes to hours. Other studies of clam harvesting found no measurable changes to nitrogen, sulfide, phosphate (Tarr 1977; Goodwin 1977; Goodwin and Shaul 1980), dissolved oxygen (Tarr 1977), or total organic carbon (Sparsis et al. 1993) measurements related to cultivation of sediments. Similar to these other findings, our study indicated that changes to sediment chemistry related to dredging were generally immediate and short-lived, either resolving before our first postdredge sampling on the following day or in the case of hydrogen flux and organic carbon, within several weeks of the dredging event.

Benthic invertebrate species composition can vary on large (e.g., bioregionalisation) or small (habitat) spatial scales. Sediment grain size, environmental water chemistry, and habitat characteristics can influence the presence of marine organisms. Sediment grain size is considered one of the most important variables defining habitat suitability for macrobenthic fauna (Ysebaert et al. 2002; Compton et al. 2009; Kraan et al. 2010). In our study, sediment grain size was the best single explanatory factor for the observed variability in both the total benthic and molluscan assemblages, respectively, but explained just approximately 14% of the total variability for each of the two groups. We found that adding oxygenation of sediments to this multiple regression model improved explanatory power slightly for the total benthic assemblage, but not for the molluscan subset. A shift from oxygenated sediments to hypoxia has been reported to result in a migration of mobile epibenthic species with echinoderms and most crustaceans. Sedentary annelids, molluscs, and cnidarians are more tolerant of oxygen depletion (Rosenberg et al. 1991; Diaz and Rosenberg 1995). Occasionally, there can be a reduction in benthic species at higher oxygen levels (>100 μM) that can be correlated with a reduction in observed species due to subtoxic effects (Thrush et al. 1992), but that was not observed in these sediments. Green et al. (2013) suggest that calcite and aragonite saturation state might be better indicators of molluscan settlement than the chemical parameters and grain size classifications we measured. Further studies are required to identify specific factors that may be influencing molluscan settlement at dredged sites.

Our BACI-style experiment found that one-time hydraulic shellfish dredging, as conducted by a commercial harvester in Connecticut, had minor effects on the sediment chemistry of a leased clam bed, which resolved within days or weeks. Sediment grain size and oxygen concentration influenced benthic community structure and molluscan abundance more strongly than any of the other chemical parameters we measured.


  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Literature Cited

We thank Captains R. Alix and W. Schreiner for vessel operations; S. Auscavitch, S. DeCarli, M. Dixon, J. Esposito, J. Goggins, K. Harper, T. L. Nguyen, D. Redman, J. Reidy, G. Sennefelder, and A. Wu for technical support; and L. Williams of the Jesse D. Shellfish Company for dredging our study site and allowing us to sample their leased clam beds. The State of Connecticut, Department of Agriculture, Bureau of Aquaculture's D. Carey and T. Barrell helped coordinate experimental dredging and shellfish marking beds.

Literature Cited

  1. Top of page
  2. Abstract
  3. Materials and Methods
  4. Results
  5. Discussion
  6. Acknowledgments
  7. Literature Cited
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  • Coen, L.D. 1995. A review of the potential impacts of mechanical harvesting on subtidal and intertidal shellfish resources. South Carolina Department of Natural Resources, Marine Resources Research Institute. p. 46 pp. + 3 appendices.
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