Effects of current speed, shell length and type of sediment on the erosion and transport of juvenile softshell clams (Mya arenaria)

Journal of Experimental Marine Biology and Ecology 349 (2007) 12 – 26 www.elsevier.com/locate/jembe

Effects of current speed, shell length and type of sediment on the erosion and transport of juvenile softshell clams (Mya arenaria) Philippe St-Onge, Gilles Miron ⁎ Département de biologie, Université de Moncton, Moncton, Nouveau-Brunswick, Canada E1A 3E9 Received 16 September 2006; received in revised form 14 February 2007; accepted 19 March 2007

Abstract The erosion and transport of juvenile softshell clams (Mya arenaria) was studied in a laboratory flume in relation to free-stream velocity (0, 7, 16, 29 and 35 cm s− 1), shell length (0–5, 5–10, 10–15, 15–20 mm) and type of sediment (mud, sandy-mud, sand and gravel). Our results showed that these factors interact together on the erosion of clams from the sediment. Juveniles were eroded in great numbers in sand while mud retained them more easily. Bedload transport was initiated at speeds of 16 cm s− 1. Most of the clams were eroded in sandy sediments at speeds of 29 and 35 cm s− 1. The smallest individuals were highly vulnerable to erosion compared to the other size classes studied. A results-based model using the logistic regression statistics was proposed. This allowed the estimation of erosion probabilities for a given hydrosedimentary environment. A field validation of the model was then carried out. Field results confirmed the importance of free-stream velocity, shell length and type of sediment on the erosion rate of clams. The differences observed between predicted and field results suggest that the model underestimated the erosion rate in the field. Results are discussed in the context of hydrosedimentary environments found off the eastern coast of Canada. © 2007 Elsevier B.V. All rights reserved. Keywords: Erosion; Mya arenaria; Recruitment; Sediment; Shell length; Softshell clams; Tidal currents

1. Introduction The study of marine invertebrates inhabiting softbottom environments is a complex task when assessing their population dynamics. For instance, the characteristics associated with a given type of sediment may change the general behaviour of endobenthic organisms in regard to recruitment processes. In contrast to what may be observed in hard-bottom habitats, invertebrates can use the depth dimension offered by sediments to their benefit. Individuals may avoid predators more ⁎ Corresponding author. Tel.: +1 506 858 4542; fax: +1 506 858 4541. E-mail address: [email protected] (G. Miron). 0022-0981/$ - see front matter © 2007 Elsevier B.V. All rights reserved. doi:10.1016/j.jembe.2007.03.020

easily as well as escape desiccation and/or other rapidly changing parameters within a tidal environment. Marine infauna may also benefit from a soft-bottom environment by having more flexibility in the choice of a suitable habitat once settled (Rodríguez et al., 1993). One of the difficulties associated with the use of softbottom habitats, however, is that endobenthic organisms become more vulnerable to bedload transport compared to those living in hard-bottom habitats. This is particularly true for small individuals. This may lead to their erosion from the sediment – and subsequent transport – and thus strongly affect their recruitment success (e.g., Emerson, 1991; Armonies, 1994; Commito et al., 1995a,b; Roegner et al., 1995; Turner et al., 1997; Commito and Tita, 2002; St-Onge et al., 2007).

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

Erosion of endobenthic organisms may be affected by many factors including sediment stability (e.g., Emerson, 1990; Widdows et al., 2000) and hydrodynamics (e.g., Matthiessen, 1960; Eckman, 1983, 1990; Sleath, 1982; Hannan, 1984; Eskin and Palmer, 1985; Butman, 1986; Miller and Sternberg, 1988; Gross et al., 1992). Both parameters are known as the most important driving forces in bedload transport processes (Emerson and Grant, 1991). Bottom topography (Eckman, 1979, 1983; Savidge and Taghon, 1988; Abelson and Denny, 1997) and a large variety of biological adaptations are also known to be important: e.g., burrowing depth (Medcof, 1950; Zwarts and Wanink, 1989; Auffrey et al., 2004), byssal thread drifting (Sigurdsson et al., 1976; Lane et al., 1985; Armonies, 1988; Beukema and de Vlas, 1989), predator–prey relationships (Hunt and Mullineaux, 2002; Hunt, 2004a) or interactions with other benthic organisms (e.g., Dunn et al., 1999). Post-settlement transport of benthic organisms on intertidal flats has been observed in various bivalve species (e.g., Sigurdsson et al., 1976; Lane et al., 1985; Beukema and de Vlas, 1989; Martel and Chia, 1991; Armonies and Hellwig-Armonies, 1992; Commito et al., 1995a,b). For instance, Matthiessen (1960) showed that juveniles of the softshell clam Mya arenaria from 2 to 15 mm were vulnerable to constant location changes in the intertidal zone. Emerson and Grant (1991) confirmed that bedload transport occurs for the same species on intertidal sandflats, showing high numbers (N2500 ind m− 1 d− 1) of juvenile individuals (6 to 28 mm) in bedload traps. Roegner et al. (1995) demonstrated in a flume experiment that current speed had an effect on the erosion rates of M. arenaria post-larvae (b250–300 μm) buried in the top layer of the sediment. Hunt (2004b) showed similar results in another flume experiment for M. arenaria smaller than 3 mm. Though improvements have been made in the study of the effect of hydrodynamics and sediment types on bivalve erosion, the process is still not well understood. Roegner et al. (1995) and Hunt (2004a,b), for instance, did not use in their studies a large variety of sediment types in which natural populations of M. arenaria are observed (e.g. mud, sandy-mud, sand and gravel). Their studies did not focus, as well, on juveniles between 2 and 20 mm. An integrated study of these factors would allow us to better predict the erosion of clams from the sediment and in turn increase our understanding of recruitment processes for populations of endobenthic bivalves. The present study was initially carried out in a laboratory flume to determine the erosion rates of preburied juveniles of M. arenaria in relation to current

13

speed, shell length and type of sediment. We predict that the erosion rates of clams will increase with increasing free-stream velocity and decrease with increasing shell length and size of sediment particles. A statistical model was developed to predict the erosion probability of a juvenile clam of a given size in a given hydrosedimentary environment. Predictions from the model were then compared to erosion rates observed in the field. 2. Methods 2.1. Flume characteristics All experiments were carried out in a custom made Plexiglas© racetrack-type flume. The flume had a maximum capacity of 250 L and was 20 cm wide at all points. It was oval in shape bearing 75-cm-long straight channels connected by two semi-circular sections, with an inner core diameter of 44 cm and an outer core diameter of 89 cm. Water flow was generated by friction in one of the straight sections by a series of nine 3-mmthick parallel Plexiglas© wheels. Wheels were controlled by a 12 V DC shunt motor and a 4A gear box with a pulse width modulation speed control. The wheels could generate a constant water flow over the working section for speeds between 0 and 40 cm s− 1. The working station was a built-in opening (40 × 20 × 10 cm) in which a sediment box of similar size could be installed. The working section was located in the second straight section of the flume. A series of parallel walls were installed in the curved section upstream of the working section to minimize a side-wall effect observed during preliminary trials due to the width of flume/depth of boundary layer thickness ratio (Jumars and Nowell, 1984; Muschenheim et al., 1986). The sediment box was divided into four sections (19 × 3 × 10 cm) parallel to the flow to separate each type of sediment for a total working surface of 228 cm2. It had a removable lid and attached handles to allow easy installation and retrieval in and from the flume. Once installed, the sediments contained in the box were levelled with the bottom floor of the flume. During trials, the flume was filled with artificial seawater (28 ppt, 18 °C). 2.2. Collection of softshell clams and sediments Juvenile clams were collected in the field using a 1mm meshed sieve. Clams were sorted into four separate size classes based on their shell length (SL): 0–5, 5–10, 10–15 and 15–20 mm. Individuals from the smallest size class were retrieved from mats of Enteromorpha

14

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

intestinalis in St-Andrews (NB, Canada). All remaining juveniles were sampled from Côte-à-Fabien in Kouchibouguac National Park. Once collected, the clams were transported to the laboratory and kept at 4 °C in aerated seawater that was replaced weekly. Clams were conditioned in 18 °C seawater for a minimum of 24 h prior to their treatment in the flume. Dead clams were also used to discriminate active behavioural processes from passive erosion. Clams of each size class were put into a formalin-based solution (4%) to kill them prior to their use in the experiment. The types of sediment used in the present study (mud, sandy-mud, sand, gravel) correspond to various habitats in which natural softshell clam beds are found off the coast of New Brunswick (Robert and Smith, 1980; LeBlanc and Miron, 2005, 2006). The mud and gravel sediments were sampled from Anthony's Cove (St. John) while sandy-mud and sand sediments were collected in l’Aboiteau and Sandy Beach (Cap Pelé). Each sediment type was sieved to eliminate the macrofauna. Sediments were kept in seawater at 4 °C to minimize consolidation effects and stirred biweekly to prevent hydrogen sulfide (H2S) from building up. Each

type of sediment was taken directly from the refrigerated stock and texture homogenized prior to its use in the flume. Grain-size composition is presented in Fig. 1. The mud sample was very heterogeneous and mostly composed of silt particles (b 63 μm). The sandy-mud sample was mostly composed of particles between 0.125 and 0.5 mm. The sand sample was composed of particles between 0.25 and 1 mm while the majority of particles from the gravel sample were N0.5 mm. 2.3. Current speed Five current speeds (Uf) were chosen for the study: 0, 7, 16, 29 and 35 cm s− 1. These free-stream velocities were measured 2.5 cm below the water surface and are identical to the velocities used by Roegner et al. (1995) in a similar study on M. arenaria. This speed range is similar to tidal currents occurring in Atlantic Canada (Roegner et al., 1995; personal observation). The flow pattern above the working section was analyzed to calibrate the flume with a water depth of 21 cm. We used a Marsh–McBirney current meter at several tri-dimensional points. Water velocities were

Fig. 1. Distribution of particle sizes for the various types of sediment used in the study: (A) mud; (B) sandy-mud; (C) sand; and (D) gravel.

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

measured at thirteen separate depths above the sediment for each free-stream velocity. These data were then used in the “law of the wall” model (Jumars and Nowell, 1984) to estimates shear velocities (u⁎) in addition to creating vertical velocity profiles (Fig. 2). The mean shear velocities observed in our flume were similar to those observed by Roegner et al. (1995). 2.4. Flume experiment Ten juvenile clams from each size class were handplaced in the sediments and levelled with the sediment surface in each of the sediment box compartments. Clams b 20 mm are known to stay near the sediment surface in the wild (first 2 cm) (Medcof, 1950; Zwarts and Wanink, 1989; Zaklan and Ydenberg, 1997). All individuals were positioned so that their shell opening was facing the current. The order in which the various types of sediment were placed in the box was chosen at random to avoid a position effect that could occur over the working section of the flume. The rectangular lid was then screwed on the top of the sediment box to reduce water movement at the sediment-water interface and thus avoid the displacement of individuals while it was placed into the water-filled flume. The lid was then carefully removed to expose the clams to the watercolumn. Clams were given a 10 min acclimation period to adjust to the flume environment before water movement was initiated. Each trial had a running time of 60 min. Once the trial was completed, power was turned off and the sediment box taken out after the flow came to a complete stop. The lid was screwed into the

15

top of the sediment box to avoid the loss of individuals before retrieval. Each layer of sediment was then collected and sieved through a 1-mm mesh sieve and the remaining clams counted. Clams that were swept by the current, completely uncovered but not swept away or half-buried were labeled as eroded. Individuals that are completely uncovered or half-buried are often swept away in the wild. This is especially true during the ebb tide when tidal currents are high. Partially and completely uncovered clams have to wait for the flood tide to burrow successfully (St-Onge et al. 2007). Eighty randomly achieved runs were carried out: 5 free-stream velocities × 4 size classes × 4 replicates, all types of sediment being offered during an experimental run. Twenty additional runs were carried out similarly with the dead clams: 5 free-stream velocities × 4 size classes (no replication). 2.5. Field experiment An additional study was carried out in the field to validate predictions from the erosion model developed using the flume data. The validation was carried out in the fall of 2004 and 2005 in two different sites with contrasting tidal regimes: (1) Côte-à-Fabien (Kouchibouguac National Park), Northumberland Strait (hereafter CF) and (2) Anthony’s Cove (St. John), Bay of Fundy (hereafter AC). These sites are easily accessible and were previously characterized by LeBlanc and Miron (2005, 2006). Wooden boxes (15 × 15 × 13 cm) were completely filled with one of the four sediment types (mud, sandy-

Fig. 2. Flow profiles (mean ± SE, n = 60) taken at thirteen different heights above the sediment for four different free-stream velocities.

16

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

mud, sand and gravel). Three replicates were used for each type of sediment for a total of 12 boxes. The boxes were then seeded by hand with 10 clams from each of the three larger size groups (5–10, 10–15, 15–20 mm) and 5 clams from the smaller size group (0–5 mm). All clams were completely buried and were flush with the sediment surface. All boxes were then randomly placed in a row, parallel to the shore line, and put flush with the ocean floor at low tide. Boxes were retrieved after a complete tidal cycle (i.e., flood tide, slack water period and ebb tide). Clams found unburied or half-buried were considered as eroded and were therefore discarded. Twelve sediment boxes seeded similarly were used as control treatments to discriminate active behaviour that may lead individuals to leave the sediment from passive erosion. These boxes were submerged into a pool filled with stagnant seawater once the tide level had reached the treatments. The control treatments were retrieved once the tidal cycle over. All boxes were thereafter brought to the laboratory and sieved (1-mm). Clams that remained completely buried during the tidal cycle were then measured and counted by size class. Tidal currents during the flood and ebb tides were measured with a Marsh–McBirney current meter. The sensor of the probe was placed 3 cm above the bottom. Field erosion rates were then compared to predictions from the logistic model for a given clam size in a given sediment type using the maximum tidal current speed measured at each study site.

Table 1 Summary of a three-way ANOVA for a split-plot design carried out on the mean proportion of juvenile clams (Mya arenaria) that got eroded and transported during a constant 60 min of flow Source of variation

SS

df MS

Free-stream 273,460.39 4 velocity (F) Shell length (S) 769,660.57 3 F×S 26,577.17 12 Main plot error 129,120.50 60 Type of 161,327.63 3 sediment (T) F×T 244,567.17 12 S×T 67,934.23 9 F×S×T 126,075.98 36 Sub plot error 371,736.38 180 Total 2,170,460.00 319

F

P

68,365.10

31.77

b0.0001

256,553.52 2214.76 2152.01 53,775.88

119.22 1.03 – 26.04

b0.0001 0.4349 – b0.0001

20,380.60 7548.25 3502.11 2065.20 –

9.87 3.65 1.70 – –

b0.0001 0.0003 0.0134 – –

in the ANOVA procedure did not seem to affect significantly the erosion rates (F-statistics analysis), all data corresponding to a similar treatment were pooled together to facilitate the description of the results (Figs. 3 and 4). The independent variables of the logistic regression model were shell length, free-stream velocity and type of sediment. The model included seven terms (three main effect and four interaction terms) and one intercept. The following equation was used to convert the odds ratio of the regression model:     l ¼ e gðlÞ = 1 þ e gðlÞ ; ð1Þ

2.6. Statistical analysis The main effects of current speed, shell length and type of sediment, as well as their interactions, were analyzed using the number of clams that got eroded during the 60 min flume run as the dependent variable (α = 0.05). Data were processed with rank transformations. To account for the split-plot design caused by the use of a single free-stream velocity and a single size class per experimental run, the response variables were analyzed with a GLM procedure (SAS Institute, 1982) (see Table 1). The experimental run was included in the model as a random factor. Residuals were examined to ensure that postulates for normality and homogeneity of variances were met. Data were also analyzed using a binary logistic regression (Hosmer and Lemeshow, 2000) to predict the erosion rate of a clam of a given size class for a given hydrosedimentary environment. The dependant variable in the model was the erosion outcome for each clam (n = 3200), which was labelled as eroded (Y = 1) or not (Y = 0) after the end of a flume run. Since the run effect

where μ is the erosion probability of a buried juvenile clam and g(μ) the logit link function of the regression (Jaccard, 2001). When all independent variables are continuous, the g(μ) parameter is determined using: gðlÞ ¼ b0 þ b1 S þ b2 F þ b3 T þ b4 SF þ b5 ST þ b6 FT þ b7 SFT ;

ð2Þ

where β0 defines the constant coefficient of the regression (intercept), β1 the coefficient of the independent focal variable shell length (S), β2 the coefficient of the first moderator variable free-stream velocity (F), β3 the coefficient of the second moderator variable type of sediment (T). The coefficients β4, β5, β6 and β7 are related to SF, ST, FT and SFT interaction terms, respectively. However, since the variable type of sediment (T) is a nominal predictor, dummy variables had to be used to represent group membership (Hosmer and Lemeshow, 2000; Jaccard, 2001). Three dummy variables were created: DM (mud), DSM (sandy-mud) and DS (sand).

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

17

Fig. 3. Percentage of eroded Mya arenaria (mean ± SE, n = 40) from different shell sizes under different current speeds in (A) mud, (B) sandy-mud, (C) sand and (D) gravel.

Gravel was used as the reference group. Eq. (2) was then modified to: gðlÞ ¼ b0 þ b1 S þ b2 F þ b3 DM þ b4 DSM þ b5 DS þ b6 SF þ b7 SDM þ b8 SDSM þ b9 SDS þ b10 FDM þ b11 FDSM þ b12 FDS þ b13 SFDM þ b14 SFDSM þ b15 SFDS ;

ð3Þ

with different coefficients for each term and each dummy variable. The significance of each term was tested with a forward conditional stepwise procedure (α = 0.05). Three different parameters (−2 log likelihood, Cox and Snell R2 and Nagelkerke R2) were used in the analysis as relative measures-of-fit for the logistic regression model. The fit of the model improved with decreasing values of −2 log likelihood and with increasing values of both R2 parameters. A Receiver Operating Characteristics (ROC) curve (Zweig and Campbell, 1993; Hosmer and Lemeshow, 2000) was also drawn from the estimated

erosion probabilities to assess whether or not the regression model was a good predictor. The curve was drawn by plotting the probability of correctly predicting a positive erosion of any given clam (sensitivity) and the probability of incorrectly predicting a negative outcome (1 — specificity) for numerous cutpoints (Hosmer and Lemeshow, 2000). According to Hosmer and Lemeshow (2000), a model with an area ranging between 0.8 and 0.9 is an excellent discriminator. The general shape of the curve may also reveal some information about the overall accuracy of the model. The closer the curve is from the upper left-hand corner of the figure, the better the accuracy of the model is (Zweig and Campbell, 1993; Hosmer and Lemeshow, 2000). All statistical analyses concerning the logistic regressions and the ROC curve were carried out with SPSS 11.5© for Windows©. The predicted and observed field erosion rates for all 64 possible combinations of sediment types (4), shell length (4) and field studies (4: two dates, two sites) were tested for correlation with the Pearson product-moment correlation coefficient (Zar, 1999). A two-tailed one

18

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

Fig. 4. Percentage of eroded live (mean ± SE, n = 4) and dead Mya arenaria (n = 1) for different types of sediment. L1, L2, L3 and L4 represent the shell length class: L1: 0–5 mm; L2: 5–10 mm; L3: 10–15 mm; L4: 15–20 mm. S0, S7, S16, S29 and S35 represent the free-stream velocity: S0: still water; S7: 7 cm s− 1; S16: 16 cm s− 1; S29: 29 cm s− 1; S35: 35 cm s− 1. Significant differences between live and dead clam erosion rates are noted with an asterisk.

sample t-test (Pagano, 2004) was used to test significant differences (α = 0.05) between the mean (n = 4) erosion rates of live clams (μ) and the unreplicated erosion rate for dead clams (μ0) for a given shell length in each hydrosedimentary trial. 3. Results 3.1. General observations 3.1.1. Erosion rates The ANOVA results indicated that free-stream velocity, shell length and type of sediment had a significant interaction effect on the erosion rates of juvenile clams (Table 1). Erosion was usually more frequent with increasing flow speed (Fig. 3). The response, however, varied in relation to the size of the clam as well as to the

sediment in which it was buried. For instance, clams N5 mm were not eroded in mud (Fig. 3A). Clams from the 0–5 mm size class started to be eroded at 7 cm s− 1 (20%). However, 20% of the clams were uncovered in still water as well. Erosion reached, for the latter size class, a plateau (40%) at speed ≥ 29 cm s− 1. Clam erosion in sandy-mud (Fig. 3B) was similar to what was observed in mud. However, clams N 5 mm started to be eroded at speeds ≥ 29 cm s− 1. An erosion peak (40%) was also observed at 7 cm s− 1 for clams from the 0–5 mm size class. Again, 20% of clams from the 0–5 mm size class were uncovered in still water. Clam erosion rates were high in sand (Fig. 3C). Erosion increased with increasing flow speed regardless of the size class. Clams from the 0–5 mm size class were always eroded in greater numbers compared to the other size classes. Almost 40% of clams of this size class were

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26 Table 2 Summary of characteristics related to the logistic regression model and goodness-of-fit (− 2 log likelihood, Cox and Snell R2 and Nagelkerke R2) for each step of the forward conditional stepwise procedure Product terms added (+) or removed (−)

− 2 log likelihood

Cox and Snell R2

Nagelkerke R2

Type of sediment × free-stream velocity (+) Shell length (+) Shell length × free-stream velocity (+) Type of sediment × shell length (+) Type of sediment (+) Type of sediment × shell length × free-stream velocity (+) Free-stream velocity (+) Shell length × free-stream velocity (−)

2219.098

0.103

0.186

1994.448 1937.324

0.164 0.178

0.297 0.323

1890.388

0.190

0.345

1846.695 1809.01

0.201 0.211

0.365 0.382

1804.992 1805.276

0.212 0.212

0.384 0.384

An interaction product term was added to the model (+) or removed from it (−) at each step. The final step corresponds to the best optimized model possible.

uncovered in still water. Erosion of clams N 5 mm started at 16 cm s− 1. Clam erosion in gravel (Fig. 3D) was more important for the 0–5 mm size class, starting at the speed of 7 cm s− 1 . The variability of the response was, however, important. Erosion for clams N5 mm was usually below 10%. Erosion rates were closely related to bedload transport. Practically no movement on the sediment bed was observed at speeds of 0 and 7 cm s− 1. A few grains of sand moved at 16 cm s− 1, while heavy bedload transport occurred at speeds of 29 and 35 cm s− 1. Bedload transport was similar in sandy-mud but was less intense than what was observed in sand. Practically no bedload transport was observed in mud or gravel. As the sediment was being eroded, some clams could rebury further into the sediment. Most clams, however, were exposed to stronger flows and therefore eroded more easily. Clam erosion usually occurred after the erosion of sediments. There were still a small number of half-buried clams, in the absence of bedload transport, that were labeled as eroded because they actively uncovered themselves. 3.1.2. Dead versus live clams Erosion rates observed with dead clams were generally similar to those in the live clam trials (Fig. 4). Our results, however, showed that significant differences

19

were observed in 11 of the 80 trials: 3 in sandy-mud; 4 in sand; and 4 in gravel. Variability in the erosion rates of live clams was more important in sand. Two of these 11 trials showed a higher erosion rates for the live clams (sand: L1S0 and L1S16) than for the dead ones (Fig. 4). The remaining nine trials showed higher erosion rates for dead clams. 3.2. Erosion predictions 3.2.1. Flume study Results from the logistic regression analysis showed that almost all terms, including the interactions, played an active role in the model. The forward conditional stepwise procedure allowed us to optimize the fit of the regression model by eliminating the shell length × freestream velocity interaction (β6SF term) from the model (Table 2). The coefficients generated by the analysis (Table 3) were introduced in Eq. (3). The following logistic regression equation was then used: gðlÞ ¼ 1:852  0:412S þ 0:032F þ 71:495DM þ 7:14DSM þ 1:83DS  70:715SDM  6:072SDSM  1:15SDS  1:931FDM  0:193FDSM þ 0:04FDS þ 1:934SFDM þ 0:173FDSM þ 0:036SFDS :

ð4Þ

Shell length (S) can be substituted in the regression to estimate the erosion probability for a given shell length: i.e., “1” for clams between 0 and 5 mm, “2” for clams between 5 and 10 mm, “3” for clams between 10 and 15 mm and finally, “4” for clams between 15 and 20 mm. Extrapolation for clams N 20 mm is not

Table 3 Summary of the logistic regression coefficients of the intercept and each product term for the final optimized model Product term

Logistic coefficient

Shell length Free-stream velocity Mud Sandy-mud Sand Mud × shell length Sandy-mud × shell length Sand × shell length Mud × free-stream velocity Sandy-mud × free-stream velocity Sand × free-stream velocity Mud × shell length × free-stream velocity Sandy-mud × shell length × free-stream velocity Sand × shell length × free-stream velocity Intercept

− 0.412 0.032 71.495 7.14 1.83 −70.715 − 6.072 − 1.15 − 1.931 − 0.193 0.004 1.934 0.173 0.036 − 1.852

20

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

Fig. 5. Predicted juvenile clam (Mya arenaria) erosion probabilities given by the logistic regression model for (A) mud, (B) sandy-mud, (C) sand, and (D) gravel.

recommended. The same can be done for free-steam velocity (F) to estimate an erosion probability. Again, extrapolation to free-stream velocities N 35 cm s− 1 is not recommended. Finally, as explained earlier, we may substitute the dummy variable related to the type of sediment in which a given clam is buried. For instance, if a clam is buried in gravel, we then substitute every dummy variable with the value “0” since gravel was used as the reference group. Eq. (4), using odds ratio from Eq. (1), allow us to calculate an erosion probability (μ) for a given hydrosedimentary environment. The value of the logit obtained with Eq. (4) for all possible permutations of parameters can be substituted in Eq. (1) to generate 4 different tri-dimensional curves of the estimated erosion rates of juvenile clams for each sediment type (Fig. 5). Overall, the model shows that the clam erosion rate is affected by the interaction between shell length and free-stream velocity which intensity is governed by the type of sediment. The fit of the regression model is apparently good. The area under the ROC curve reached a value of 0.868 (Fig. 6).

Fig. 6. Receiver Operating Characteristics (ROC) curve for the logistic regression model with the best fit, as determined by the forward conditional stepwise procedure. The reference line represents an area under the curve of 0.5.

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

21

Fig. 7. Predicted and field erosion rates of juvenile clams (Mya arenaria) for all studied size classes (0–5; 5–10; 10–15 and; 15–20 mm of SL) in (A) mud, (B) sandy-mud, (C) sand and (D) gravel. Both field studies were carried out in 2004 (CF: Côte-à-Fabien, Northumberland Strait; AC: Anthony’s Cove, Bay of Fundy) and are presented with their corresponding value of maximum tidal current (mtc). Results from 2005 were similar.

3.2.2. Field validation study The tidal currents (mean ± SD) were fairly low in the Northumberland Strait site (CF) both in 2004 (3.77 ± 1.59 cm s− 1) and 2005 (1.13 ± 1.03 cm s− 1). The mean tidal currents reached 16.75 ± 5.91 cm s− 1 in 2004 and 14.20 ± 6.98 cm s− 1 in 2005 in the Bay of Fundy (AC). The maximum tidal current measured in each site was

used in the logistic regression model to predict an erosion rate for all size classes of juveniles in each type of sediment. Only data from 2004 are presented in Fig. 7 since those from 2005 were similar. Overall, our results showed that erosion rates observed in the field were equal or higher to rates predicted by the model in 60 of the 64 possibilities. Differences

22

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

between predicted and field rates were increasing with decreasing shell length and were less important in sand and mud than in sandy-mud and gravel. Predicted and field rates, still, varied in the same way (r2 = 0.52, P b 0.001). Individuals were also observed leaving the sediment in the field controls (no flow), particularly for the smaller size group (0–5 mm). 4. Discussion 4.1. Biological considerations Many studies have looked at the relationship between flow speed and larval settlement in softbottom environments. This was carried out for various invertebrate species (e.g., Butman, 1986; Grassle and Butman, 1989; Grassle et al., 1993; Pawlik and Butman, 1993; Eckman et al., 1994; Turner et al., 1994; Abelson, 1997; Snelgrove et al., 1998; Crimaldi et al., 2002). Although larval settlement can sometimes play a leading role in the recruitment success of endobenthic organisms (Santos and Simon, 1980), several post-settlement factors are also important in modeling community dynamics during the juvenile stages (e.g., Menge and Sutherland, 1987; Günther, 1992; Olafsson et al., 1994; Blackmon and Eggleston, 2001). Erosion and transport are determinant factors in assessing the population dynamics of intertidal invertebrates (e.g., Günther, 1992; Armonies, 1994; Commito et al., 1995a,b; Turner et al., 1997; Hunt and Mullineaux, 2002; Commito and Tita, 2002; St-Onge et al., 2007). Our results clearly indicate that free-stream velocity, shell length and type of sediment interact together to influence the erosion rates of juvenile M. arenaria. Flow speed affects the erosion of juvenile softshell clams because of bedload transport. Our results complement those from Roegner et al. (1995) on the postlarvae (b250–300 μm) of the same species. Both studies showed that juvenile clams experienced erosion and transport beginning at a speed of 16 cm s− 1 with almost total erosion at speeds of 29 and 35 cm s− 1. Hunt (2004b) also showed that softshell clams b5 mm were eroded in greater proportions as shear velocities increased. Similar effects were observed by Bell and Sherman (1980) and Eskin and Palmer (1985) on the meiofauna. The latter studies showed that intertidal organisms may be eroded and redistributed during flood tides. The present study outlines the importance of flow for juveniles up to 20 mm. As already observed by Matthiessen (1960) and Emerson and Grant (1991), we

showed that juvenile clams from a large range of shell sizes may be eroded and transported and that individuals are not secured until they reach a bigger size. The probability of remaining in the sediment increases with increasing shell length (Hunt 2004b). Lundquist et al. (2004) found similar results in a laboratory flume with the bivalve Macomona liliana. Their results showed that individuals b 2 mm were recovered in plankton nets in greater proportions than larger individuals (4–8 mm). Larger individuals bear bigger and longer siphons, which in turn allow them to bury deeper in the sediments. These individuals should then be less affected by water flow at the sediment-water interface (Medcof, 1950; Zwarts and Wanink, 1989). The erosion rates observed in this study were closely related to bedload transport (see also Hunt, 2005). Hunt (2004b) tried to predict the erosion and transport of M. arenaria by calculating an erosion threshold based on the physical characteristics of the sediment. She concluded that the erosion of softshell clams could not be solely predicted by such factors because of the clam's ability to burrow into the sediments and thus escape erosion events. In the present study, nine of the eleven trials in which differences were found between erosion rates of dead and live clams (Fig. 4) showed that dead clams were eroded at higher rates than live clams. This show that clams may actively bury further in the sediment in order to avoid erosion and transport. When bedload transport was occurring, we also often found clams deeply buried in the sediment box. Significant differences between dead and live clams were usually observed at free-stream velocities ≥ 16 cm s− 1. Roegner et al. (1995) found similar results with post-larvae at 29 cm s− 1. Our study also showed that juvenile softshell clams were actively emerging from the sediment in both flume and field control treatments. The lack of normal burrow structures, which may convey some protections from erosion, could be responsible for the clam’s emergence from the sediment. It is also known that bivalve early life-stages may actively leave the sediment and use the tidal current to relocate themselves. This contributes greatly to the colonization and recruitment of the intertidal flat. Various mechanisms have been proposed (e.g. Sigurdsson et al., 1976, Lane et al., 1985; Butman, 1987; Martel and Chia, 1991; Rodríguez et al., 1993; Lundquist et al., 2004). Our results, however, showed that N 85% of the experimental runs failed to discriminate significant differences between the erosion rates of dead and live clams (Fig. 4). This suggests that erosion and transport may be mostly governed by passive processes.

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

From the 11 trials in which we found significant differences between the dead and live clam erosion rates (Fig. 4), none was observed in mud. This suggests that passive erosion is minimized in muddy sediment, probably because of its strong retention properties and low bedload transport. This response was different in the other type of sediment. This observation is consistent with results from Roegner et al. (1995). Intertidal habitats bear various types of sediments which in turn present different cohesive properties. The erosion of softshell clams will be affected by the cohesive property of a given sediment as well and not only on its mean grain size. Many other physical characteristics may alter the cohesive properties of the sediment (Grass, 1970). Bioturbation (e.g., Nowell et al., 1981; Grant et al., 1982; Widdows et al., 2000) and various season-related factors such as ice-scouring (e.g., Anderson, 1983) are, for instance, known to affect the erosion of sediments. 4.2. Resuspension model Being capable of accurately predicting survival probabilities of intertidal invertebrates in contrasting hydrosedimentary environments could be very useful for marine ecologists and conservation biologists. Realistic erosion models may be useful to predict overall recruitment patterns of intertidal bivalves and assess more rigorously their population dynamics. This is of further interest since bivalve farms are relying more and more on hatchery-reared juveniles that are seeded in the wild (e.g., Beal et al., 1995; Congleton et al., 1999). However, complex field dynamics make it a strenuous task. Results from this study have shown that current speed, shell length and type of sediment, including their interactions, play an important role in the erosion and transport of the softshell clam M. arenaria. Our prediction curves (Fig. 5) clearly suggest that juvenile clams inhabiting sandy sediments will probably encounter a higher erosion probability compared to those buried in other types of sediment. It is also in sandy sediments that larger clams will be more likely to get eroded. This suggests, for instance, that farmers who seed their hatchery-reared individuals in sandy beaches may encounter lower survival rates than those who seed them in muddy intertidal flats. Our results-based model underestimated the erosion rates of juvenile clams in the wild. The Pearson correlation analysis, however, indicated that the predicted erosion rates varied in the same way as the erosion rates observed in the field. The discrepancies observed between both rates show that other factors may play a role in the erosion of intertidal juvenile clams. Wave action

23

and wind-induced currents (Hagerman and Rieger, 1981; Sleath, 1982; Ward, 1985; Grant and Madsen, 1986; Commito et al., 1995b; Denny, 1995), for instance, were not investigated in the flume experiments and probably accounted for most of the underestimation. The flow velocities that are associated with windinduced currents can reach impressive values over a small amount of time (Miller and Sternberg, 1988) and are usually unpredictable (Denny, 1995). They can probably induce more erosion events than tidal currents due to bedload transport (Hagerman and Rieger, 1981; Ward, 1985; Commito et al., 1995b). Duration of flow exposure during the flume experiment also contributed to underestimate erosion in the field. However, it is important to keep in mind that most of the juveniles that got eroded from the sediment in the flume experiments usually did so in the first 30 min of the experimental run. Therefore, the predicted erosion rates would not likely have been altered if the duration of the experimental runs would have been similar to the submersion time of the tidal cycles. Tidal currents are also known to vary within a unique tidal cycle (Dyer, 1970), which can explain in part the model’s underestimation of the erosion rates. Other factors such as sediment cohesiveness (Grant et al., 1982), small-scale bottom topography (Eckman, 1979) and presence/absence of natural chemicals (e.g., H2S) may also contribute to the erosion of juvenile bivalves. The accuracy of the model increased with increasing shell length. This confirms that small bivalves are also more vulnerable to other post-settlement transport factors. The small differences among the predicted and field erosion rates in mud indicates once again that this type of sediment is more stable than the others, being less affected by erosion. However, small differences between both erosion rates were also observed in sandy sediments at the AC site in the Bay of Fundy. This confirms that sand is an unstable environment under high tidal currents in relation to bedload and clam transport. 4.3. Implications for Eastern Canada The importance of current speed, shell length and type of sediment in the erosion and transport of juvenile M. arenaria may be integrated in the context of the Eastern coast of Canada. The Bay of Fundy is widely known for its high tides and heterogeneous sediments ranging from muddy tidal flats in protected coves to gravelly sediments in exposed sites. The Northumberland Strait facing the Gulf of St. Lawrence is characterized by low tidal currents and sandy beaches. Even

24

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

though the two areas are significantly different, natural populations of softshell clams can be observed in both locations (Landry, 1996; Robinson, 1997; LeBlanc and Miron, 2005, 2006). The present study tends to suggest that the hydrosedimentary characteristics of both tidal flats are able to retain endobenthic bivalve species. In fact, even though the tidal flats of the Northumberland Strait are mostly composed of sandy sediments, an environment highly susceptible to bedload transport, the tidal currents are probably too low to have a negative effect on the erosion of juvenile bivalves. The opposing scenario characterizes the Bay of Fundy. Despite rapid tidal currents, the erosion of bivalves is limited in muddy flats because of strong retention properties of the sediments. 4.4. Conclusion Further studies are needed to increase the accuracy of the erosion model for intertidal clams. The factors that were studied in the present study were important but insufficient erosion predictors. The passive/active aspect of erosion and transport should be studied thoroughly to define and quantify a behavioural variable and to integrate it in a predictive model. The relocation of intertidal benthic invertebrates after an erosion event is not properly understood as well (Savidge and Taghon, 1998; Emerson et al., 1990; Woodin et al., 1995; Coffen-Smout and Rees, 1999). Recovery studies of eroded and transported juvenile softshell clams over a tidal cycle are needed to better understand post-settlement processes in the recruitment dynamics of marine bivalve populations (St-Onge et al., 2007). Acknowledgements We wish to thank P. St-Onge for his help with the construction of the racetrack flume and A. Chiasson for the use of his current meter. We also wish to thank É. Tremblay and all the staff at Kouchibouguac National Park for their huge commitment to our project and S. LeBlanc, R. Sonier, J. Roy, N. Pelletier, S. Lévesque and M.-J. Abgrall for their help in the field. J. Lemaître, J.-S. Guénette, J. Allard, M. Mallet and G. Moreau provided helpful statistical comments. P. Archambault, H. Hunt, B. Pavey and P. St-Onge reviewed earlier drafts of this manuscript. Comments from two anonymous reviewers help increased the clarity of the text. Funding for this research has been provided by NSERC, CFI and DFO grants to Gilles Miron. The Université de Moncton provided a scholarship to Philippe St-Onge. [SS]

References Abelson, A., 1997. Settlement in flow: upstream exploration of substrata by weakly swimming larvae. Ecology 78, 160–166. Abelson, A., Denny, M., 1997. Settlement of marine organisms in flow. Ann. Rev. Ecol. Syst. 28, 317–339. Anderson, F.E., 1983. The northern muddy intertidal: seasonal factors controlling erosion and deposition — a review. Can. J. Fish. Aquat. Sci. 40, 143–159. Armonies, W., 1988. Active emergence of meiofauna from intertidal sediment. Mar. Ecol. Prog. Ser. 43, 151–159. Armonies, W., 1994. Drifting meio- and macrobenthic invertebrates on tidal flats in Königshafen: a review. Helgol. Meeresunters. 48, 299–320. Armonies, W., Hellwig-Armonies, M., 1992. Passive settlement of Macoma balthica spat on tidal flats of the Wadden Sea and subsequent migration of juveniles. Neth. J. Sea Res. 29, 371–378. Auffrey, L.M., Robinson, S.M.C., Barbeau, M.A., 2004. Effect of green macroalgal mats on burial depth of soft-shelled clams Mya arenaria. Mar. Ecol. Prog. Ser. 278, 193–203. Beal, B.F., Lithgow, C.D., Shaw, D.P., Renshaw, S., Ouellette, D., 1995. Overwintering hatchery-reared individuals of the soft-shell clam, Mya arenaria L.: a field test of site, clam size, and intraspecific density. Aquaculture 130, 145–158. Bell, S.S., Sherman, K.M., 1980. A field investigation of meiofaunal dispersal: tidal resuspension and implications. Mar. Ecol. Prog. Ser. 3, 245–249. Beukema, J.J., de Vlas, J., 1989. Tidal-current transport of threaddrifting postlarval juveniles of the bivalve Macoma balthica from the Wadden Sea to the North Sea. Mar. Ecol. Prog. Ser. 52, 193–200. Blackmon, D.C., Eggleston, D.B., 2001. Factors influencing planktonic, post settlement dispersal of early juvenile crabs (Callinectes sapidus Rathbun). J. Exp. Mar. Biol. Ecol. 257, 183–203. Butman, C.A., 1986. Larval settlement of soft-sediment invertebrates: some predictions based on an analysis of near-bottom velocity profiles. In: Nihoul, J.C.J. (Ed.), Marine Interfaces Ecohydrodynamics. Elsevier, New York, pp. 487–513. Butman, C.A., 1987. Larval settlement of soft-sediment invertebrates: the spatial scales of pattern explained by active habitat selection and the emerging role of hydrodynamical processes. Oceanogr. Mar. Biol. Ann. Rev. 25, 113–165. Coffen-Smout, S.S., Rees, E.I.S., 1999. Burrowing behaviour and dispersion of cockles Cerastoderma edule L. following simulated fish disturbance. Fish. Res. 40, 65–72. Commito, J.A., Tita, G., 2002. Differential dispersal rates in an intertidal meiofauna assemblage. J. Exp. Mar. Biol. Ecol. 268, 237–256. Commito, J.A., Currier, C.A., Kane, L.R., Reinsel, K.A., Ulm, I.M., 1995a. Dispersal dynamics of the bivalve Gemma gemma in a patchy environment. Ecol. Monogr. 65, 1–20. Commito, J.A., Thrush, S.F., Pridmore, R.D., Hewitt, J.E., Cummings, V.J., 1995b. Dispersal dynamics in a wind-driven benthic system. Limnol. Oceanogr. 40, 1513–1518. Congleton Jr., W.R., Pearce, B.R., Parker, M.R., Beal, B.F., 1999. Mariculture siting: a GIS description of intertidal areas. Ecol. Model. 116, 63–75. Crimaldi, J.P., Thompson, J.K., Rosman, J.H., Lowe, R.J., Koseff, J.R., 2002. Hydrodynamics of larval settlement: the influence of turbulent stress events at potential recruitment sites. Limnol. Oceanogr. 47, 1137–1151.

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26 Denny, M., 1995. Predicting physical disturbance: mechanistic approaches to the study of survivorship on wave-swept shores. Ecol. Monogr. 65, 371–418. Dunn, R., Mullineaux, L.S., Mills, S.W., 1999. Resuspension of postlarval soft-shell clams Mya arenaria through disturbance by the mud snail Ilynassa obsoleta. Mar. Ecol. Prog. Ser. 180, 223–232. Dyer, K.R., 1970. Current velocity profiles in a tidal channel. Geophys. J. R. Astron. Soc. 22, 153–161. Eckman, J.E., 1979. Small-scale patterns and processes in a softsubstratum, intertidal community. J. Mar. Res. 37, 437–457. Eckman, J.E., 1983. Hydrodynamic processes affecting benthic recruitment. Limnol. Oceanogr. 28, 241–257. Eckman, J.E., 1990. A model passive settlement by planktonic larvae onto bottoms of differing roughness. Limnol. Oceanogr. 35, 887–901. Eckman, J.E., Werner, F.E., Gross, T.F., 1994. Modeling some effects of behavior on larval settlement in a turbulent boundary layer. Deep-Sea Res. 41, 185–208. Emerson, C.W., 1990. Influence of sediment disturbance and water flow on the growth of the soft-shell clam, Mya arenaria L. Can. J. Fish. Aquat. Sci. 47, 1655–1663. Emerson, C.W., 1991. A method for the measurement of bedload sediment transport and passive faunal transport on intertidal sandflats. Estuaries 14, 361–371. Emerson, C.W., Grant, J., 1991. The control of soft-shell clam (Mya arenaria) recruitment on intertidal sandflats by bedload sediment transport. Limnol. Oceanogr. 36, 1288–1300. Emerson, C.W., Grant, J., Rowell, T.W., 1990. Indirect effects of clam digging on the viability of soft-shell clams, Mya arenaria L. Neth. J. Sea Res. 27, 109–118. Eskin, R.A., Palmer, M.A., 1985. Suspension of marine nematodes in a turbulent tidal creek: species patterns. Biol. Bull. 169, 615–623. Grant, W.D., Madsen, O.S., 1986. The continental-shelf bottom boundary layer. Annu. Rev. Fluid Mech. 18, 265–305. Grant, W.D., Boyer, L.F., Sanford, L.P., 1982. The effects of bioturbation on the initiation of motion of intertidal sands. J. Mar. Res. 40, 659–677. Grass, A.J., 1970. Initial instability of fine bed sand. J. Hydraul. Div. Proc. Am. Soc. Civ. Eng. 96, 619–632. Grassle, J.P., Butman, C.A., 1989. Active habitat selection by larvae of the polychaetes, Capitella sp. I and II, in a laboratory flume. In: Ryland, J.S., Tyler, P.A. (Eds.), Proc. 23rd Euro. Mar. Biol. Symp. Olsen & Olsen, Fredenborg, Denmark, pp. 107–114. Grassle, J.P., Snelgrove, P.V.R., Butman, C.A., 1993. Larval habitat choice in still water and flume flows in the opportunistic bivalve Mulina lateralis. Neth. J. Mar. Res. 30, 30–44. Gross, T.F., Werner, F.E., Eckman, J.E., 1992. Numerical modeling of larval settlement in turbulent bottom boundary layers. J. Mar. Res. 50, 611–642. Günther, C.P., 1992. Dispersal of intertidal invertebrates: a strategy to react to disturbances of different scales? Neth. J. Sea Res. 30, 45–56. Hagerman, G.M., Rieger, R.M., 1981. Dispersal of benthic meiofauna by wave and current action in Bogue Sound, North Carolina, USA. P.S.Z.N.I. Mar. Ecol. 2, 245–270. Hannan, C.A., 1984. Planktonic larvae may act like passive particles in turbulent near-bottom flows. Limnol. Oceanogr. 29, 1108–1116. Hosmer, D.W., Lemeshow, S., 2000. Applied Logistic Regression, second edition. John Wiley & Sons, New York, NY. Hunt, H.L., 2004a. Effects of epibenthic predators in flow: transport and mortality of juvenile soft-shell clams (Mya arenaria). Mar. Ecol. Prog. Ser. 279, 151–160.

25

Hunt, H.L., 2004b. Transport of juvenile clams: effects of species and sediment grain size. J. Exp. Mar. Biol. Ecol. 312, 271–284. Hunt, H.L., 2005. Effects of sediment source and flow regime on clam and sediment transport. Mar. Ecol. Prog. Ser. 296, 143–153. Hunt, H.L., Mullineaux, L.S., 2002. The roles of predation and postlarval transport in recruitment of the soft shell clam (Mya arenaria). Limnol. Oceanogr. 47, 151–164. Jaccard, J., 2001. Interaction effects in logistic regression. Sage University Paper Series on Quantitative Applications in the Social Sciences, Thousand Oaks, CA. Jumars, P.A., Nowell, A.R.M., 1984. Fluid and sediment dynamic effects on marine benthic community structure. Am. Zool. 24, 45–55. Landry, T., 1996. Mye du sud du Golfe. MPO Pêches de l’Atlantique, Rapport sur l’état des stocks 96/101F. Lane, D.J.W., Beaumont, A.R., Hunter, J.R., 1985. Byssus drifting and the drifting threads of the young post-larval mussel Mytilus edulis. Mar. Biol. 84, 301–308. LeBlanc, S., Miron, G., 2005. Spatial distribution of adult and juvenile softshell clams (Mya arenaria) in two tidally contrasted regimes in New Brunswick. Can. Tech. Rep. Fish. Aquat. Sci. 2602. LeBlanc, S., Miron, G., 2006. Bentho-pelagic distribution of early stages of softshell clams (Mya arenaria) in tidally contrasted regimes. Can. J. Zool. 84, 459–472. Lundquist, C.J., Pilditch, C.A., Cummings, V.J., 2004. Behaviour controls post-settlement dispersal by the juvenile bivalves Austrovenus stuchburyi and Macomona liliana. J. Exp. Mar. Biol. Ecol. 306, 51–74. Martel, A., Chia, F.S., 1991. Drifting and dispersal of small bivalves and gastropods with direct development. J. Exp. Mar. Biol. Ecol. 150, 131–147. Matthiessen, G.C., 1960. Intertidal zonation in populations of Mya arenaria. Limnol. Oceanogr. 5, 381–388. Medcof, J.C., 1950. Burrowing habits and movements of soft-shelled clams. Fish. Res. Board Can. Prog. Rep. Atlan. Coast. Stat. 50, 17–21. Menge, B.A., Sutherland, J.P., 1987. Community regulation: variation in disturbance, competition, and predation in relation to environmental stress and recruitment. Am. Nat. 130, 730–757. Miller, D.C., Sternberg, R.W., 1988. Field measurements of the fluid and sediment-dynamic environment of a benthic deposit feeder. J. Mar. Res. 46, 771–796. Muschenheim, D.K., Grant, J., Mills, E.L., 1986. Flumes for benthic ecologists: theory, construction and practice. Mar. Ecol. Prog. Ser. 28, 185–196. Nowell, A.R.M., Jumars, P.A., Eckman, J.E., 1981. Effects of biological activity on the entrainment of marine sediments. Mar. Geol. 42, 133–153. Olafsson, E.B., Peterson, C.H., Ambrose, W.G., 1994. Does recruitment limitation structure populations and communities of macro-invertebrates in marine soft-sediments: the relative significance of pre- and post-settlement processes. Oceanogr. Mar. Biol. Annu. Rev. 32, 65–109. Pagano, R.R., 2004. Understanding Statistics in the Behavioral Sciences, 7th edn. Wadsworth/Thomson Learning, Belmont, CA. Pawlik, J.R., Butman, C.A., 1993. Settlement of a marine tube worm as a function of current velocity: interacting effects of hydrodynamics and behavior. Limnol. Oceanogr. 38, 1730–1740. Robert, G., Smith, D.W., 1980. Surveys of soft-shell clam (Mya arenaria) populations in some closed areas of Charlotte County, New Brunswick. Can. Manuscr. Rep. Fish. Aquat. Sci. 1567. Robinson, S., 1997. Mye de la Baie de Fundy. MPO Pêches de l’Atlantique, Rapport sur l’état des stocks 96/127F.

26

P. St-Onge, G. Miron / Journal of Experimental Marine Biology and Ecology 349 (2007) 12–26

Rodríguez, S.R., Ojeda, F.P., Inestrosa, N.C., 1993. Settlement of benthic marine invertebrates. Mar. Ecol. Prog. Ser. 97, 193–207. Roegner, G.C., André, C., Lindegarth, M., Eckman, J.E., Grant, J., 1995. Transport of recently settled soft-shell clams (Mya arenaria L.) in laboratory flume flow. J. Exp. Mar. Biol. Ecol. 187, 13–26. St-Onge, P., Miron, G., Moreau, G., 2007. Burrowing behaviour of the softshell clam (Mya arenaria) following erosion and transport. J. Exp. Mar. Biol. Ecol. 340, 103–111. Santos, S.L., Simon, J.L., 1980. Marine soft-bottom community establishment following annual defaunation: larval or adult recruitment? Mar. Ecol. Prog. Ser. 2, 235–241. SAS Institute, 1982. SAS User⁎s Guide: Statistics. Statistical Analysis System Institute, Cary, North Carolina. Savidge, W.B., Taghon, G.L., 1988. Passive and active components of colonization following two types of disturbance on an intertidal sandflat. J. Exp. Mar. Biol. Ecol. 115, 137–155. Sigurdsson, J.B., Titman, C.W., Davies, P.A., 1976. The dispersal of young post-larval bivalve molluscs by byssus threads. Nature 262, 386–387. Sleath, J.F.A., 1982. The suspension of sand by waves. J. Hydraul. Res. 77, 39–55. Snelgrove, P.V.R., Grassle, J.P., Butman, C.A., 1998. Sediment choice by settling larvae of the bivalve, Spisula solidissima (Dillwyn), in flow and still water. J. Exp. Mar. Biol. Ecol. 231, 171–190. Turner, E.J., Zimmer-Faust, R.K., Palmer, M.A., Luckenbach, M., Pentcheff, N.D., 1994. Settlement of oyster (Crassostrea virginica) larvae: effects of water flow and a water-soluble chemical cue. Limnol. Oceanogr. 39, 1579–1593.

Turner, S.J., Grant, J., Pridmore, R.D., Hewitt, J.E., Wilkinson, M.R., Hume, T.M., Morrisey, D.J., 1997. Bedload and water-column transport and colonization processes by post-settlement benthic macrofauna: does infaunal density matter? J. Exp. Mar. Biol. Ecol. 216, 51–75. Ward, L.G., 1985. The influence of wind waves and tidal currents on sediment resuspension in middle Chesepeake Bay. Geo Mar. Lett. 5, 71–75. Widdows, J., Brown, S., Brinsley, M.D., Salkeld, P.N., Elliott, M., 2000. Temporal changes in intertidal sediment erodability: influence of biological and climatic factors. Cont. Shelf Res. 20, 1275–1289. Woodin, S.A., Lindsay, S.M., Wethey, D.S., 1995. Process-specific cues in marine sedimentary systems. Biol. Bull. 189, 49–58. Zaklan, S.D., Ydenberg, R., 1997. The body size burial depth relationship in the infaunal clam Mya arenaria. J. Exp. Mar. Biol. Ecol. 214, 1–18. Zar, J.H., 1999. Biostatistical Analysis, 4th edn. Prentice Hall, Upper Saddle River, NJ. Zwarts, L., Wanink, J., 1989. Siphon size and burying depth in depositand suspension-feeding benthic bivalves. Mar. Biol. 100, 227–240. Zweig, M.H., Campbell, G., 1993. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clin. Chem. 39, 561–577.