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Every year large amounts of sand are extracted from the North Sea to meet the demand for construction and nourishment activities. Potential ecological effects of these sand mining activities have to be examined and reported in Environmental Impact Assessments (EIAs). A secondary environmental effect of sand mining is an increase in fine sediment concentrations. Increased concentrations of fines can affect water quality by increasing turbidity and changing the relative composition of organic and inorganic particulate matter in the water column and by reducing primary production by limiting light penetration. Many bivalves are filter feeders that are capable of continuously filtering food and other particles out large volumes of water. Indigestible or excess material is egested as pseudofaeces. If an impact assessment is to be made of the possible effects that an increase in the concentration of fines could have on bivalve populations, extensive knowledge of how such concentrations influence life history parameters of the bivalves is essential. In this case the effect of suspended sediment concentrations on the activity of filter feeding bivalves (e.g. clearance, ingestion, pseudofaeces production and growth) is studied. Deterministic models are presented to describe the effect of various suspended sediment concentrations on the model species chosen, the blue mussel (Mytilus edulis).



    Title: Cause-effect chain modelling Sand Mining - Mussels: Modeling the effect of dredging on filter-feeding bivalves
    Location: No actual project.
    Date: not relevant (no actual project)
    Companies: IMARES and Royal HaskoningDHV
    Costs: not relevant (no actual project)
    Abstract: A deterministic model is presented that describes the effect of fine sediment on the model species chosen, the blue mussel (Mytilus edulis). These models can be used to predict the impact of dredging on filterfeeding bivalve populations.
    Topics: Ecological studies, Ecology - fish/shellfish, Environmental impacts, Environmental management, Impact assessment, Marine mining, Risk assessment, Risk management, Silts and sediments, Water quality

    Project Objective and Approach

    The objective of this project is to study the effect of suspended sediment concentrations on the activity of filterfeeding bivalves (e.g. clearance, ingestion, pseudofaeces production and growth). The aim is to develop deterministic models which describe the effect of suspended sediment on the blue mussel (Mytilus edulis). As the blue mussel is a common and well-studied species of commercial importance, it can be regarded as an indicator species for filterfeeding bivalves. Note, however, that although the processes of filterfeeding and particle selection are comparable for other suspension-feeding lamellibranchiate bivalve species, the parameterizations and rates will differ (Cranford et al. 2011).

    An extensive literature search was made to identify potential effects of sand mining activities on the blue mussel. Two deterministic models are presented and their behavior is compared with data from the literature. This comparison was primarily meant to get an impression of the order of magnitude of the rates and the nature of the relationships. 

    These models, when properly tuned to the local situation, can be used to investigate or predict the impact of dredging on filterfeeding bivalve populations. The results can be used to decide how much increase in suspended solids is acceptable and what the best period to carry out dredging and nourishment activities is. 

    Project Solution

    In order to calculate the effect of dredging activities on growth and development of a mussel, a Dynamic Energy Budget (DEB) model can be used to simulate the impact of increased suspended sediment concentrations on individual mussels (i.e. community effects are not taken into account). The DEB model includes a functional response that describes the energy uptake of a filterfeeding bivalve as a function of food and silt concentration. The patterns of the functional response are quite comparable with observations reported in the literature.

    Governance context

    Potential ecological effects of sand mining activities have to be examined and reported in Environmental Impact Assessments (EIAs) and can be taken into account in the project development and design stage. The DEB-model, as demonstrated in this case study, can be used to assess potential effects of dredging activities on bivalve populations.


    Effects of dredging on blue mussels

    Increased suspended solid concentrations

    Sand extraction activities lead to a release of fine sand and mud particles into the water column. During the dredging process a sand-water mixture is pumped up from the seabed into the hold of the dredging vessel. Although most of the sandy part of this mixture settles in the hold, the excess transport water containing fine particles of up to 150 μm flows back into the sea. Whilst sand particles (>63 μm) settle relatively quickly on the seabed, the mud particles (<63 μm) remain suspended much longer in the water column. These suspended particles cause a ‘dredging plume’ near the dredging vessel. As a result of tidal currents and wave action, this dredging plume will be spread over a larger area. After settling on the seabed, the mud particles can easily be stirred up by waves or currents, e.g. during storms.

    Sand extractions in the North Sea mainly take place beyond the 20 m depth contour, i.e. at 20 km or more offshore. Sand extractions can increase mud concentrations by releasing suspended sediments into the water column. A direct effect of increased suspended particle concentrations in the water column is a higher turbidity level and less light penetration. This may affect phytoplankton productivity and consequently food supply to higher trophic levels. The actual impact may be local and restricted in time, although when dredging takes place at the seaward end of an estuary, for instance, a larger water mass may be affected (Essink 1999). Potential ecological implications consist of significant decreases in biomass and productivity of phytoplankton, zooplankton and filter-feeding benthos such as Mytilus edulis. For instance, deposition of sediment layers of 1-2cm thickness can result in increased mortality (Bijkerk 1988). Another important effect of sand extraction is the increased mud concentration that can clog the filter apparatus of shellfish and impede growth. Although filter-feeders, such as M. edulis, grow naturally within turbid nearshore waters where the total particulate matter (TPM) of fine sediment can reach temporary maxima of up to about 300 mg/l (Hawkins et al. 1998), anthropogenic environmental disruptions such as sand extraction may have a substantial impact of M. edulis.

    Apart from the TPM released during dredging, seawater always contains a certain background concentration of TPM which is not constant, but fluctuates due to wave action, current velocities, tide and river discharges. In addition to the TPM-concentration, phytoplankton concentrations also influence the transparency of seawater. The concentration of phytoplankton can be limited by the availability of nutrients or by the light intensity in the water column. The light intensity in the water column depends on the light intensity at the water surface and the water transparency. If light intensity is the limiting factor for primary production, an increase of the TPM-concentration (leading to less transparency) may also lead to a decrease of phytoplankton concentrations.

    To what extent the cumulative effect of increased suspension of silt, deposition of sediment, potential changes in substrate composition and food availability (i.e. primary productivity) will affect filter feeders as M. edulis depends on their capacity to sort edible particles from non-edible particles. If we are able to clarify how various processes are intrinsically related and affect M. edulis ecologically and ecophysiologically, we can use models to identify the potential consequences of sand mining for bivalve species.

    Ecology of blue mussels (Mytilus edulis)

    Blue mussels (Mytilus edulis) are widely spread in European waters, extending from the White Sea, Russia as far as south as the Atlantic coast of Southern France (also see Figure 1). This distributional pattern is the result of this species’ ability to withstand wide fluctuations in salinity, desiccation, temperature, and oxygen tension, in combination with high fecundity, extensive larval and post-larval dispersal capability, fast growth and their ability to attach by byssus threads to non-specific substrates and to one another (Gosling 1992). As a result, M. edulis can occupy a broad variety of microhabitats, expanding its zonation range from the high intertidal to subtidal regions and its salinity range from estuarine areas to fully oceanic seawaters. Its climatic regime varies from mild, subtropical locations to frequently frozen habitats. These characteristics make that M. edulis often is a very significant and abundant element of the ecosystem in many inter-tidal and sub-tidal habitats (Gosling 1992).

    The typical distribution of M. edulis in intertidal habitats appears to be mostly controlled by biological factors (predation, food competition). When predators are lacking, subtidal aggregations of M. edulis can reach high local densities and individuals attain large sizes in a relatively short period of time. In the wild, M. edulis settles in patches with open spaces in between, quickly building a dense population referred to as ‘mussel bed‘.

    Feeding and food selection by filter feeders

    Filterfeeders pump the water over their gills through the motion of the lateral cilia (fine moving hairs) at their gills. The pumping rate is actively controlled by the activity of the cilia , the size of the shell gape, the exhaling siphon area and the inter-filamentary distance of the gill (Cranford et al. 2011).

    Mytilus edulis are non-selective filterfeeders, meaning they do not discriminate between individual food particles. They feed by actively filtering particles from the water (for reviews, see Cranford et al. 2011; Jørgensen 1996), which passes into and out of the mantle cavity through the frilled siphons (or sipho, Figure 2a and b). The gills retain all particles greater than 2 – 5 μm with 100% efficiency (Bayne et al. 1977; Vahl 1972) and the filtered material is then transferred to the food grooves (ciliary tracts) on the gills and on to the labial palps (Figure 2a). The function of the labial palps is the continuous removal of materials from the lamellar food tracts, whether to be ingested as food or to be rejected as pseudofaeces (Foster-Smith 1974). Respiration simultaneously occurs as this stream of water passes over the mussels’ gills. Phytoplankton cells both living and dead, constitute the main source of food, but other sources of carbon such as decomposed macrophytes or resuspended detritus may also supplement their diet. Pseudofaeces can comprise inorganic matter, such as silt, or excess phytoplankton cells, egested under high cell concentrations (e.g. ~>8.5x 103 cells/ml (Rhodomonas sp.) or under increased silt concentrations (Clausen and Riisgård 1996).

    Mussels have been shown to be able to adapt their palp size to variable total particulate matter (TPM)-concentrations (Essink 1999). Furthermore, M. edulis can adapt its filtration and ingestion rate to the particle concentration (Clausen and Riisgård 1996) and particle size (Strohmeier et al. 2012) in the water. At very low particle concentrations (< 0.25 mg/l (Thompson and Bayne 1974; Widdows 1978), all suspended material larger than 2μm is filtered by the gill, ingested through the mouth and transported to the digestive gland for digestion. As the TPM or seston concentration increases, the digestive gland cannot digest and assimilate all the material entering the stomach. Such excess material, after bypassing the digestive gland, is transported through the gut undigested and rejected as intestinal faeces (Bayne et al. 1993; Vanweel 1961). The ratio of intestinal to glandular faeces, therefore, increases with increasing ingestion rate (mg/h), which is reflected in a decline in assimilation efficiency (Thompson and Bayne 1974; Widdows 1978).

    Ingestion rate increases with increasing particle concentration and organic matter content (Bayne et al. 1993) until a threshold value dependent on body size and ~4 mg/l) is reached, above which further material filtered by the gills is carried away from the mouth by rejection tracts on the labial palps and deposited as pseudofaeces (Thompson and Bayne 1974). The amount of pseudofaeces produced can range from zero rejection at 3 mg/l to about 40% rejection at seston concentrations of ~6-10 mg/l for low organic content (~0.75 mg/l) (Bayne et al. 1993). It has been shown that for an average mussel of 3 cm length maximum filtration occurs at TPM-concentrations of ~125 mg/l. At ~225 mg/l the filtering capacity decreases to ~30% and ceases at a TPM concentration of ~250 mg/l (Widdows et al. 1979). More recent studies did not test the effect of such high TPM concentrations on mussels, but, Bayne et al. (1993) showed that TPM concentration above the critical value of 4 mg/l resulted in an increased rejection (pseudofaeces production) with time (Table 1).  

    Table 1: Pseudofaeces production (expressed as % rejection) for mussels (4-5 cm) in 3 experiments (CI, CII and CIII (_Bayne et al. 1993)._


    TPM concentration (mg/l)

    % rejection at 2d

    % rejection at 12d













    The selection efficiency, i.e. the efficiency with which filtered material is sorted in organic and inorganic fractions prior to ingestion, is shown to decrease with increasing organic content of the TPM. The assimilation efficiency, the efficiency by which the organic fraction of ingested material is absorbed by the animal, increases with the increase in concentration of particulate organic matter (POM) (Bayne et al. 1993).

    Effects of increased concentration of suspended solids

    The results of the literature research on the effects of an increased concentration of suspended solids on blue mussels can be found in section 2.4 of Case Study Mussels - Modeling the effect of dredging on filter-feeding bivalves, which addresses:

    • clearance rates,
    • ingestion rates,
    • pseudofaeces production,
    • respiration rates,
    • assimilation efficiency
    • and growth

    Energy Budget Model

    Dynamic Energy Budget (DEB) model for mussels

    Standard DEB model

    Functional responses of filter-feeding bivalves to variations in seston have been discussed by numerous authors (e.g. Bayne et al. 1987; Foster-Smith 1975; Navarro and Iglesias 1993; Newell et al. 1989; Riisgård 2001b; Shumway et al. 1985) and implemented into physiological models (Campbell and Newell 1998; Hawkins et al. 2002; Scholten and Smaal 1998). Some of these models are based on the DEB theory (Maar et al. 2009; Rosland et al. 2009; Saraiva et al. 2011; Troost et al. 2010).

    The generic dynamic energy budget (DEB) model has been developed by Kooijman 30 years ago (Kooijman 1986; Kooijman 2000; Kooijman 2010). The DEB model describes the energy flow through an organism as a function of its size, its development stage and environmental conditions. An individual organism is described by the state variables structural body volume V (cm3), Reserves E (Joule) and Reproduction (Joule) (Figure 3). While the processes of the DEB model are generic, the parameters are species specific (Lika et al. 2011).

    The organism acquires energy from food by assimilation. The energy that is not assimilated by the organism is released through defecation. The assimilated energy is first stored into reserves (blood, glycogen). From the reserves, the energy is mobilized into growth, development and maintenance. A fixed fraction (κ) of the energy flow from the reserves is used for growth and somatic maintenance, but the priority to maintenance. The rest of the energy flow from the reserves (1-κ) is spent on maturity maintenance and reproduction (gamete production and spawning). Juveniles spend this energy to maturation.

    A key process is the assimilation rate of the food. In DEB, this is generally described by a Holling type II functional response. The scaled functional response (f) is the ratio between food uptake rate (in Joules) and the maximum food uptake rate (in Joules) and varies between 0 (no food uptake) and 1 (maximum food-uptake rate). At a food concentration X = Xk, the functional response equals 0.5.

    DEB model for filter feeding bivalves

    Suspension feeding bivalves obtain their energy by pumping water with suspended organic particles over their gills. Edible particles are selected using palps and the non-edible fraction of particles is released in the form of pseudo-faeces. The energy that is not assimilated by the bivalve is released via faeces.

    In DEB models, the effect of inorganic particles can be incorporated in the formulation of a scaled functional response (Kooijman 2006; Wijsman 2011; Wijsman and Smaal 2011).


    Where X is the food concentration, expressed in (μg chl-a/l), and X k  is the half saturation constant (μg chl-a/l) when no particulate inorganic matter is present, Y is the concentration of particulate inorganic matter expressed in mg/l and Y k  is the saturation constant for the particulate inorganic matter (mg/l).

    As can be seen from Figure 4 and Figure 5 the scaled functional response increases with food (expressed as Chl-a concentration) and decreases with the particulate inorganic matter concentration. The model is in accordance with the Synthesizing Units concept introduced in the DEB theory by Kooijman (1998; 2000; 2010). This model assumes that handling inorganic particles costs time for the filtering apparatus and that this goes at the expense of time available for food particle handling (Kooijman 2006). With this approach it is possible to model the effect of inorganic particles on the growth of shellfish, although it does not describe the process of filtration and the production of pseudofaeces and faeces explicitly.  

    Mechanistic approach

    Saraiva et al. (2011) have developed a mechanistic approach to model filtration by bivalves and their production of faeces and pseudofaeces based on the Synthesizing Units concept. The model allows for various fractions of the filtered material (e.g. silt, algae, zooplankton, detritus). In this example we only use silt (X0) and algae (X1).

    Feeding is split into separate processes:

    • Filtration: pumping of water and filtration of the particles by the gills.
    • Ingestion and pseudo-faeces production: selection the edible particles and disposal of inedible parts.
    • Assimilation and faeces production: influx of energy into the reserve pool and production of faeces.

    The Case Study Mussels - Modeling the effect of dredging on filter-feeding bivalves   focuses on filtration, ingestion and pseudofaeces production.



    DEB model: results for varying environmental conditions

    A baseline model simulation was run with a standard DEB model for mussels, extended with the formulation of clearance rates (volume of water cleared of particles per unit time) and pseudofaeces production as described in Wijsman et al (2012). The model was forced with environmental conditions (Temperature, Chlorophyll-a and Particulate Inorganic Matter) from model calculations for the North Sea (Schellekens 2012) at location Schouwen 4 near the seabed (Figure 6). The model was run from May 1st, 2007 to December 31st, 2011. As can be seen from Figure 6, the temperature varies more or less sinusoidally between about 6 ˚C in winter and about 18 ˚C in summer. The Chl-a concentration has a peak in early spring and a second peak in summer. Particulate Inorganic Matter is highest in winter due to the wind conditions. The resulting scaled functional response fluctuates between about 0.1 in winter and 0.8 in spring and summer.

    Table 2: Overview of primary DEB parameters used in the model

    The results of the DEB model show that mussel growth is mainly influenced by temperature and Chl-a. Growth is highest during summer, when temperatures are highest (Figure 7). In winter the mussels do not grow in shell length and their weight even decreases, mainly due to the poor food conditions. Reserves are built-up during spring and summer and decrease during winter. Spawning may occur already in the second year, but is higher in subsequent years. The combined dynamics of length, reserves and gonads are reflected in the weight of the mussels. 

    The dynamics of clearance rates and production of pseudofaeces are presented in Figure 8. Highest clearance rates (about 3 l/hr) are achieved by the largest mussels and in winter. Although in general the activity of the mussels is low due to the low temperatures, the low concentrations of Chl-a in winter lead to high clearance rates. Since the concentration of Particulate Inorganic Matter is high, the production of pseudofaeces is also high.

    Scholten and Smaal (1998) compute clearance rates for mussels as a function of seston concentrations in the Oosterschelde, Marennes-Oléron and Upper South Cove using the Emmy model. This model is based on detailed information of food uptake and food processing by mussels. In this study, clearance rates in the Oosterschelde seem to be highest in autumn, when the activity of the mussels is still high and Chla/sestion ratios are already low.

    DEB model: effect of increased suspended sediment concentrations

    In order to study the effect of increased Particulate Inorganic Matter on the growth and development of the mussels, three alternative model scenarios are run and compared to the baseline scenario. In all scenario’s the same amount of suspended matter is released, but the scenarios differ in the timing.

    • Continuous extra release of Particulate Inorganic Matter of 16.67 g/l (= 200/12).
    • Pulse increase of 200 g/l in June of each year
    • Pulse increase of 200 g/l in January of each year

    The resulting forcing functions of Particulate Inorganic Matter for the scenarios are presented in Figure 9 together with the concentrations from the baseline scenario. The other forcing functions, temperature and chl-a were kept the same as in the baseline scenario.

    The resulting clearance rates and pseudofaeces production are presented in Figure 10, which shows that the pulse inputs cause an increase in Particulate inorganic matter, and a decrease of clearance rates. The decrease is more pronounced when the pulse input takes place in January (blue lines). The pulse inputs have a positive effect on the pseudofaeces production.

    The continuous release of Particulate Inorganic Matter and the Pulse release in June have comparable effects on mussel growth, where the effect on weight is more pronounced than on length (Figure 11). The pulse release in January has almost no effect on mussel growth.


    Discussion and recommendations

    Impact of suspended sediment on filterfeeding

    The impact of dredging activities on filterfeeding bivalves is studied by a combination of literature research and modeling. The increased suspended sediment concentration in the water decreases the efficiency of the filtration process, since part of the filtered material is rejected and excreted in the form of faeces and pseudofaeces. Laboratory studies show that the clearance rate by filterfeeding bivalves decreases with increasing particle concentration. Laboratory studies also show that the production of pseudofaeces increases with increased silt content. As a result of the decreased feeding efficiency, the growth and development of filterfeeding bivalves will be reduced and this might have a knock-on effect on fish and birds that depend on the bivalves as a food source. 

    It can be concluded from this study that low concentrations of particulate inorganic matter already have an effect on the food-uptake rate. This is because the filterfeeding shellfish need to invest time and energy processing the inorganic matter. Short-term increases of particulate inorganic matter have less impact on the growth performance of the shellfish compared to a continuous increase. The timing of dredging activities is also important. In the winter period, when the activity of the shellfish is low, the impact of increased suspended sediment concentration is much less than during summertime. 

    Under natural conditions, many factors may influence the filtration rate of bivalves. Feeding under laboratory conditions may not always accurately reflect in situ filtration where a wide spectrum of changing environmental factors and species interactions may influence the feeding behavior. Field measurements with benthic chambers and benthic tunnels have been used to overcome this problem and validate the lab measurements. In laboratory conditions, filterfeeding bivalves are easily disturbed, which is reflected in the clearance rates. Therefore, it is important to have a good set-up of the laboratory experiments. 

    The present study is believed to reflect important basic features of mussels’ feeding behavior in nature where phytoplankton is the main source of nutrition. Among the many parameters that may affect the in situ feeding behavior, phytoplankton biomass (expressed as chl-a concentration) seems to be the most important. Yet, high concentrations of silt/seston leading to pre-ingestive rejection/pseudofaeces production, for instance, may also affect the feeding of mussels in estuaries and exposed coastal waters. 

    Although there is still no general agreement regarding physiological control of water pumping in response to (very) high concentrations of particles in the ambient water, present consensus tends to be that the filtration rate is high and constant, that is, basically autonomous, between a lower critical level and an upper seston concentration threshold. However, it remains to be clarified if the reduced filtration rate at high seston concentrations is caused by physiological regulation (supporting maximum assimilation and growth) or overloading (adversely affecting food uptake and growth) (Riisgård 2001a). 

    A substantial body of knowledge is available on the feeding behavior of filterfeeding bivalves. Physiological models (e.g. Hawkins et al. 2002; Rueda et al. 2005) integrate this knowledge into more complex formulations. Alternatively, in DEB models a relatively simple description using a scaled functional response is applied. The scaled functional response describes the energy uptake rate as a function of food concentration. The effect of suspended sediment concentration can be incorporated in the functional response. The functional response does not include any knowledge on the feeding behavior of the organism. The results of the formulation, however, compare well with laboratory observations. 

    Processes as clearance rates and pseudofaeces production are no standard output of DEB models. The formulation of Saraiva et al. (2011) provides an interesting method to model these processes using the DEB formulation. This approach can be used efficiently to quantify the impact of increased suspended sediment concentrations due to dredging activities on the growth and activity of filterfeeding bivalves. 

    Chapter 3 describes how the impact of changes in silt and/or phytoplankton concentrations on the growth of an individual blue mussel (Mytilus edulis) can be modeled in a deterministic way, using the DEB-model. In cases where worst-case or conservative assumptions are made to model ecological impacts deterministically, however, the use of a probabilistic instead of a deterministic approach can have several advantages (Van Kruchten 2008). For example: in a probabilistic approach worst-case assumptions can largely be prevented by incorporating the uncertainty itself in the cause-effect chain modeling. In such case, deterministic modeling may lead to an overestimation of the ecological effect, whereas the probabilistic modeling results give information on the probability of occurrence of possible effects. Although in the DEB-model uncertain parameters or variables can be identified, realistic instead of conservative assumptions are made to deal with these uncertainties. In order to quantify the uncertainty, Monte Carlo simulations with varying parameter values can be made. 

    Yet, the results of the model presented in chapter 3 can be considered a realistic estimate of the impact of the (fictitious) dredging project on blue mussels. The added value of applying a probabilistic analysis to this case is limited and will not make a difference between a highly conservative and a realistic estimate of the impact on mussels. A probabilistic analysis might be used to quantify the uncertainty margin of the final prediction. Because a probabilistic analysis is quite laborious, however, a sensitivity analysis instead of a probabilistic analysis is recommended to give insight into the uncertainty margins of the results.


    Because mussels are able to adapt to different silt concentrations in the water column, it is important that impact studies take into account the natural variability of silt concentrations the area, as well as the time spans during which these conditions may remain modified. Short term increases in suspended sediment concentration will have less impact on the food intake of shellfish than a continuous release.

    This study is primarily focused on blue mussels as a model species for suspension-feeding lamellibranchiate bivalves. It is assumed that the processes will be comparable for other species and that only the values of the parameters will differ. However, it is good to check this assumption using literature data from other species.

    The models that were used in this study were not directly calibrated with field observations and literature information on filtration rates and pseudofaeces production. It would be an improvement to perform an additional calibration with the appropriate data.


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