# Evaluating ecosystem functioning of a long-term dumping site in the Bay of Seine (English Channel)

Aurore Raoux, Noémie Baux, Jean-Philippe Pezy, Pierre Balay, Sandric Lesourd, Jean-Claude Dauvin

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## To cite this version:

Aurore Raoux, Noémie Baux, Jean-Philippe Pezy, Pierre Balay, Sandric Lesourd, et al., Evaluating ecosystem functioning of a long-term dumping site in the Bay of Seine (English Channel). *Ecological Indicators*, 2020, 115, 10.1016/j.ecolind.2020.106381. hal-03420719

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1 *Ecological Indicators*

2

3 Evaluating ecosystem functioning of a long-term dumping site in the Bay of Seine (English Channel)

4 Aurore Raoux¹*, Noémie Baux¹,²,³, Jean-Philippe Pezy¹, Pierre Balay², Sandric Lesourd¹, Jean-Claude

5 Dauvin¹

6

7 ¹Normandie Univ, UNICAEN, Laboratoire Morphodynamique Continentale et Côtière, CNRS UMR

8 6143 M2C, 24 rue des Tilleuls, 14000 Caen, France.

9 ²Normandie univ., UNICAEN, Laboratoire des Sciences Appliquées de Cherbourg, EA 4253, 50100

10 Cherbourg, France.

11 ³Conservatoire National des Arts et Métiers, INTECHMER, 50100 Cherbourg, France.

12 ⁴Cellule de Suivi du Littoral Normand, CSLN, 53 Rue de Prony, 76600 Le Havre, France.

13

14 * Corresponding author: aurore.raoux@unicaen.fr

15

16 ABSTRACT

17

18 The impact of 70 years of dumping harbour dredged material on ecosystem functioning was
19 compared to a control site (non-impacted zone). A combination of indices (Shannon-Wiener
20 diversity, Pielou evenness, BO2A, AMBI benthic indices) and modelling (Ecopath models) generated
21 Ecological Network Analysis indices were used to detect the dumping operations effects. ENA indices
22 showed that dumping operations appear to have a relatively limited impact on the structure and flow
23 pattern of the local food web. In fact, only small variations between the two sites are revealed by a
24 comparison of ENA indices between the impacted and non-impacted zone. This result could be
25 explained by the fact that the Bay of Seine is historically characterized by a high level of human
26 activities, which have led to an increase in resilience through time to face these multiple pressures.

27 AMBI and BO2A indices (of the sediment fauna) did not allow a clear distinction between impacted
28 and non-impacted zone while species richness, abundance, biomass and Shannon-Wiener diversity
29 index values were significantly higher in the non-impacted zone which is in accordance with the small
30 variations of ENA indices between the two zones and revealed a local and limited impact. Our results
31 suggested that a combination of several tools should be used to detect the true impacts and to
32 conduct diagnosis of the ecological status of dumping deposit in a coastal area permanently stressed
33 under natural and anthropogenic forcing.
34

34
**KEYWORDS:** Dredged material disposal; harbour activities; Ecopath model; Ecological Network; Analysis. Benthic indicators; impacted zone; non-impacted zone; Bay of Seine.

# 1. Introduction

Coastal ecosystems are heavily disturbed by human activities (fishing, traffic maritime, aggregate extraction, and introduction of non-native species) and are among the most anthropized area of the earth (Halpern et al., 2008). Among these activities, the dumping of dredged material represents one of the most important problems in coastal zone management (Marmin et al., 2014, 2016). In fact, harbours need to carry out regularly dredging to maintain sufficient water depth in the basins and access channels in order to allow safe navigation and port activities. The dredged sediment can be deposited onshore or at sea if they do not contain hazardous products (Marmin et al., 2014, 2016). However, these dumping of dredged materials from ports can lead to major physical, sedimentological and biological disturbances on marine ecosystems (de Jonge, 1983; O'Connor, 1998; Essink, 1999; Marmin, 2013; Marmin et al., 2014, 2016; de Jonge et al., 2014). For instance, dumping operation could lead to the destruction of local habitats or changes in species composition (Marmin, 2013). The impact degree depends on numerous factors, such as the method and intensity of dumping operations, the resulting turbidity, the particle size of dumped sediment, water depth and currents, as well as the similarity between the dredged materials and the initial natural sediment at the dumping site (Essink, 1999; Marmin et al., 2014, 2016; Baux et al., 2019). In addition, it is worth to note that this impact differ greatly from one site to another (Harvey et al., 1998; Pezy et al., 2017, 2018). Thus, it is difficult to draw general conclusions about disposal effects on ecosystem and it seems that evaluation must be done on a case-by-case basis (Harvey et al., 1998).

Studies on the consequences of dredging on benthic communities are common (de Jonge, 1983; Harvey et al., 1998; Roberts et al., 1998; de Jonge et al., 2014) whereas the impacts of dumping dredge materials on the whole ecosystem are rarely found in the literature (Pezy et al, 2017, 2018). In fact, monitoring programs are often focused on indicators based only on species diversity and relative abundance of the dominant species. However, understanding, how a disturbance can propagate through an entire ecosystem and can lead to changes in ecosystem structure and function is essential to ensure a good management strategy as well as to achieve a Good Environmental Status required by the Water Framework and Good Ecological Status required in the Marine Strategy Framework Directive. The assessment of changes in ecosystem structure and functioning following dumping operations can be achieved through trophic web modelling tools coupled with Ecological Network Analyses (ENA) indices which allow to quantify interactions between the different
components within an ecosystem as well as to reveal emergent trophic web properties (Pezy et al., 2017). In fact, this type of joint analysis has been widely used to analyse trophic web changes over time in response to a wide range of perturbations such as: fisheries (Bentley et al., 2017, Corrales et al., 2017, Preciado et al., 2019), invasive species (Baird et al., 2012; Corrales et al., 2017), harbour extensions (Tecchio et al., 2016), offshore wind farms (Raoux et al., 2017, 2019; Pezy et al., 2018), eutrophication (Schückel et al., 2015), dumping (Pezy et al., 2017, 2018). In addition, ENA indices could also serve ecosystem state long-term monitoring.

The eastern part of the Bay of Seine (English Channel) is highly impacted by the presence of harbour activities, fishing and sediment extraction (Dauvin et al., in press). Two harbours are located close to the mouth of the Seine estuary: the Grand Port Maritime de Rouen (GPMR) and the Grand Port Maritime du Havre (GPMH). The Havre harbour authorities dredge between 2 and 2.5 million m³ of sediment each year in the basins and channels access of the Havre harbour and deposit this material in an offshore dumping zone named Octeville, located 8 km at sea from Le Havre (Marmin et al., 2014; Baux, 2018, 2019). The dumping Kannik site in the North Channel of the Seine estuary was used by GPMR until 2016 (4 to 4.5 million m³ per year) and it is now replaced by the Machu site (Pezy et al., 2018). Assessing dumping impacts on marine ecosystem is essential to achieve proper management of the sector and for the conservation of the ecosystem. At the experimental site of Machu in the eastern part of the Bay of Seine, Pezy et al. (2017, 2018) showed how trophic web models coupled with ENA indices, could be developed as an add-on to the use of environmental impact assessment to better understand the ecological effects of dredged materials at the local level.

Pezy et al. (2017) investigated the structure and functioning of Machu site before and after the experimental dumping operations. In addition, they also investigated the short-term changes of benthic indices during the dumping period distinguishing impacted and influenced zones from the non-impacted zone (Pezy et al., 2018). One of the main results showed a high resilience (amount of disturbance a system can cope with and still remain in the same state, see Holling, 1973; Elmqvist et al., 2003) of the benthic habitat after a one-year dumping phase at the Machu site. Other authors that postulated that recovery rates had been relatively rapid in environmentally stressed or high-energy ecosystems (Flemer et al., 1997; Ray and Clarke, 1999) supported this result.

Unlike the Machu experimental site, with a one year BACI (Before-After-Control-Impact) approach, Octeville dumping site was used historically since 1947, with large volumes of dumped sediments (average 2-2.5 million m³ y⁻¹). Dumped sediment on Octeville site come from Le Havre harbour basins, composed with a large part of mud and muddy sands (average of fine fraction <63 µm: 77.5 %, in 2014; Brasselet, 2014), in comparison to dumped sediment on Machu site, sampled in medium sand areas of the Seine estuary (Marmin et al., 2014, 2016). These fine deposited particles on Octeville dumping site are more mobile in a strong hydrodynamic area (Baux et al., 2019), in
comparison with coarser and less mobile sediments on Machu site. Another difference between the
two sites was that there was no historical biological data before dumping operations on the Octeville
site. Thus, it is necessary to compare the ecosystem after dumping operations with a non-impacted
zone. It is also interesting to compare the ecosystem structure and function of the Octeville site (long
term dumping operations and fine deposited particles impacted a large area and a high volume of
dumped sediment) with the Machu site (short term dumping operations and low volume). This
comparison is possible because both sites present the same geographical and oceanographic context
(tidal environment and sedimentary input from Seine estuary).

Using the same methodology as Pezy et al. (2017, 2018), we investigated the dredged materials
effect on the Octeville dumping zone ecosystem structure and function, selecting impacted stations
(directly under the influence of sediment disposal) and non-impacted stations (without direct
influence of sediment disposal and with the same physical and biological characteristics with
impacted station). We also compare the Octeville ecosystem structure and the functioning with the
Machu ecosystem in order to study the potential difference or similarity between the two
ecosystems and to evaluate if the methodology used by Pezy et al. (2017, 2018) is relevant on the
Octeville dumping site.

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## 2. Materials and methods

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### 2.1. Study area

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Situated on the French coast of the English Channel, the Bay of Seine forms an approximate
quadrilateral of 5000 km², 50 km from north to south and 100 km from west (eastern coast of
Cotentin) to east (western extremity of the Pays de Caux). The Bay of Seine never exceeds 30 m in
depth. It is characterized by a macrotidal regime, with strong tidal currents. The tidal range varies
between 3.0 to 7.5 m (Le Hir et al., 2001). The tidal currents average between 0.5-1.0 m s⁻¹ in the
southern sector of the bay, and their intensity gradually diminishes towards the eastern part of the
Bay of Seine (Salomon and Breton, 1991, 1993). Benthic communities are distributed in response to
hydrodynamic and sedimentary gradients, from a muddy fine sand community in coastal shallow
waters to a sandy gravel community further offshore (Gentil and Cabioch, 1997; Lesourd et al., 2003).
The major freshwater inputs into the bay are due to the Seine River, the discharge of which varies
seasonally from a maximum of up to 2,000 m³ s⁻¹ in winter to a minimum of 100-200 m³ s⁻¹ in
summer. Moreover, the Seine estuary is a major source of fine particles in the eastern part of the Bay
of Seine (Lesourd et al., 2016). The suspended particulate matter found in the Seine estuary and in
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the eastern part of the Bay of Seine comes from several different sedimentary sources such as marine, fluvial, fossil or estuarine (mixed; Dubrulle et al., 2007; Baux et al., 2019).

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The Octeville dumping site is located in the eastern part of the Bay of Seine, at 8 km from Le Havre between the Cap de La Hève and Cap d'Antifer (Figure 1). Since the middle of the twenty century, it has been used for dumping sediment dredged from Le Havre harbour. This site was chosen for its proximity to the harbour and the strong hydrodynamics in this zone, which leads to the natural dispersal of fine particles (Méar et al., 2018). The seafloor of the dumping site is mainly covered with muddy sand and sandy mud. A historical deposition area associated with a shoal (-5 m), with gravel and pebble is present on the south-eastern part of the dumping site (Baux et al., 2019). For the daily maintenance of the harbour, an amount of 2-2.5 10⁶ m³ y⁻¹ of fine sediments are dumped since 2006 (following the harbour extension, Port 2000; Marmin et al., 2014; Baux et al., 2019). The dumped sediments are heterometric (with multimodal particle size spectrum with a mixture of several particles size). For instance, the mud accounts for 70% of the sediment at the dumping site (Brasselet, 2014). However, a part of the sediments is dispersed outside the dumping zone over a large distance due to the strong hydrodynamic regime. Baux et al. (2019) showed that parts of dumped fine particles are mainly dispersed to the offshore and a smaller part to the northeast and the south. For these authors, the dumped sediments impact is local and limited to the dumping site and to the area directly around the dumping site. The GPMH dumping strategy has evolved over time to minimize impact. Currently, sediment are deposited to the north, north-west, and south-west of the dumping site, applying to a system of "boxes", in which the sediment are distributed in a thin layer (average elevation of between 0.1 to 0.6 m per box per year; Baux, 2018; Baux et al., 2019).

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## 2.2. *Sampling procedures*

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### 2.2.1. Benthic macrofauna

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From August 2016 to September 2017, sampling was carried out during six surveys: three in August, October and December 2016 and three in April, June and September 2017 (Baux, 2018). The sampling plan was carried out on at six stations, three located outside the impacted area in the non-impacted zone (R23, R21, R43; Figure 1) and three in the impacted zone (GJ, IJ, HK; Figure 1). Benthic invertebrates were sampled with a Smith McIntyre grab (0.1 m²) and three replicates were collected at each station. Sieving was performed on board using a circular 1mm mesh. The retained material was preserved in 10% formalin until the final treatments in laboratory. The samples were then sorted, and the organisms were identified at species level when possible. The biomass of each
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species was determined and expressed in terms of g of Ash-Free Dry Weight (AFDW) per m² (loss of weight of dry organisms after 5h at 500°C). Ash Free Dry Weight biomass was converted to carbon content using a conversion factor of 0.518 (Brey, 2001).

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<Figure 1>

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## 2.2.2. Fish and cephalopods

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Biomass data for fish were sampled with a bottom otter trawl (with an opening width of 8 m) by the Cellule de Suivi du Littoral Normand (CSLN, unpublished data). The sampling plan was carried out on eight dates: March, June, August and November 2016 as well as in March, June, September and December 2017. At each of these dates, three hauls were carried out in the non-impacted zone (F, G, H; Figure 1) and two in the impacted zone (C and E; Figure 1). The biomass was given for the area covered by the trawl, which corresponds to the haul length multiplied by the trawl width (8 m). For each campaign, total biomass in wet weight is divided by the number of individuals of each species to obtain the individual wet weight. A conversion factor of 0.35 is used to convert both wet weights into dry weights and into carbon contents (Boët et al., 1999). For cephalopods, a conversion factor of 0.192 was used to convert wet weights into ash free dry weights (Brey et al., 2010). Then ash free dry weight biomass was converted to carbon content using a conversion factor of 0.518 (Brey, 2001).

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## 2.3. Biotic indices

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The community structure analysis was based on the taxonomic richness, the Shannon-Wiener diversity index H' and the Pielou evenness index J'. For each zone, the macrofauna species richness corresponded to the total number of species recorded in three 0.3m² stations on six dates. Both indices H' using log₂ base and J' were calculated for each station for the non-impacted and the impacted zone. Concerning the fish, the abundance was given as the number of individuals collected per meter square (ind.m⁻²), whereas the biomass corresponds to Ash Free Dry Weight per square meter (g.m⁻²). The abundance and biomass were calculated per haul for each date.

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The AZTI Marine Biotic (AMBI) index (Borja et al., 2000) and the Benthic Opportunistic Annelids Amphipods (BO2A) index (Dauvin et al., 2016; Dauvin, 2018) were also calculated to assess the Ecological Quality Status of the benthic habitat.

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## 2.4. Statistical analysis

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The non-parametric Kruskal-Wallis test was used to find differences in benthic macrofauna between the non-impacted and the impacted zone in terms of species richness, abundance, biomass, Piélou's evenness index J', the Shannon-Wiener diversity index H', AMBI and BO2A. On the same line, Kruskal-Wallis test were also used to assess the differences in fish biomass and abundance between the stations in the non-impacted and impacted zone.

## 2.5. Trophic web modelling approach

The Ecopath with Ecosim approach and software was used to estimate the carbon flows in the two trophic webs, i.e. for the non-impacted and for the impacted zone (Polovina, 1984; Christensen et Pauly, 1992). Ecopath is a mass-balance (neglecting year-to year changes in biomass compared to flows) single-solution model (returning only one value per flow) in which the ecosystem is represented by functional groups, which can be composed of species or species groups with ecological or biological similarities. Each compartment is parameterized using its biomass data (B, gC·m⁻²), its production to biomass ratio (P/B, year⁻¹), its production to consumption ratio (P/Q, year⁻¹) or its consumption to biomass ratio (Q/B, year⁻¹), and a diet matrix (DCij) which establishes the interactions between predators and preys in the system (Christensen and Walters, 2004). The parameterization of an Ecopath model is based on satisfying two equations. These equations are based on an assumption of mass-balance (energy conservation). The first equation [Equation (1)] describes the production of each compartment in the system as a function of the consumption ratio (Q/B) of its predators (j), the fishing mortality (Yi, gC m²), the net migration (Ei; emigration – immigration, year⁻¹), the biomass accumulation (BAi, year⁻¹), and its natural mortality (1 - EEi). EE corresponds to the Ecotrophic Efficiency or the proportion of biomass consumed in the system for each compartment in the system.

$$B\left(\frac{P}{B}\right)_i = \sum_j B_j\left(\frac{Q}{B}\right)_j DC_{ij} + Y_i + E_i + BA_i + B_i\left(\frac{P}{B}\right)_i (1 - EE_i) \quad (\text{Eq. 1})$$

The second equation [Equation (2)] describes the energy balance within a compartment.

$$Q_i = P_i + R_i + U_i \quad (\text{Eq. 2})$$

The energy balance of each group in equation 2 is assured by making consumption of the i'th group (Qi) equal to the sum of its production (Pi), respiration (Ri, gC·m⁻²), and excretion of unassimilated food (Ui).
It is worth to note that a pedigree routine was implemented in Ecopath to categorize the origin of the different parameters (B, P/Q, Q/B, DC) input and specify the likely uncertainty associated with this input (Christensen and Walters, 2004). Based on it an overall index of model quality can be obtained. Lower pedigree values (i.e., 0.16) corresponded to a model constructed with data coming from other models or other ecosystems, while high values (i.e., 0.7) indicate that the model was constructed with local data (Morissette, 2007).

Finally, it is worth to note that Ecopath is a single solution model and so direct statistical comparisons is not possible.

## 2.6. Biological compartment definition and input parameters

Functional groups definition and aggregation were based on similarities between species in their ecological and biological features. The model was made of 15 functional groups including: four groups of fish (piscivorous, demersal, benthic feeders and planktivorous), seven groups of invertebrates (one cephalopod, five groups of benthic invertebrates and one meiofauna group), one group of zooplankton, one group of bacteria, one group of phytoplankton and one group of detritus.

### 2.6.1. Fish compartments

Fish were divided into four functional groups: piscivorous, demersal, benthic feeders and planktivorous. Q/B and P/B ratios were taken from Mackinson and Daskalov (2007). The diet matrix was constructed mainly using the stomach contents given in literature data (Cachera, 2013) and Pezy (2017) both studies coming from the eastern part of the English Channel.

### 2.6.2. Invertebrate compartments

#### Cephalopods

Cephalopods were grouped into a single functional group. Q/B and P/B ratios were derived from another study focused on the EC (Carpentier et al., 2009). Diet compositions were compiled according to the de Pierrepont et al. (2005) and Daly et al. (2001) studies.

#### Benthic invertebrates
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Species were grouped into five functional groups: omnivorous/scavengers, predators, filter feeders, selective deposit-feeders and non-selective deposit-feeders. P/B, Q/B, and dietary data were derived from another study focused also on the eastern part of the English Channel (Garcia, 2010).

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## Meiofauna

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The mean annual biomasses of meiofauna, as well as the P/B and Q/B ratios were obtained from the literature for a similar sediment habitat in the eastern part of the Bay of Seine (Rybarczyk and Elkaïm, 2003).

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## Zooplankton, bacteria, Primary producers, and detritus

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Data for these four compartments were obtained from literature (zooplankton: Rybarczyk and Elkaïm, 2003; bacteria: Chardy, 1987; McIntyre, 1978; Phytoplankton: Rybarczyk and Elkaïm, 2003 and detritus: Pauly et al., 1993).

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### 2.6.3. Balancing the Model

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The initial models were not balanced, since they were some Ecotrophic Efficiencies (EE) greater than 1. For instance, the Fish Planktivorous Biomasses were left to be estimated by the model after setting their Ecotrophic Efficiency to 0.90. The estimated biomasses were higher than the input data first entered during model construction. This can be partly explained by the fact that the bottom otter trawl deployed during the CSLN surveys is not fully adapted to capture these species, the abundance of which is thus likely to be underestimated. In addition, further adjustments for balancing the models were achieved exclusively by changes in the diet composition matrix in order to equalize the mass balances regarding the criterion that EE must be lower than 1 as the diet data was the source with the more uncertainty.

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### 2.64. Ecological Network Analysis

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Ecological network analysis (ENA) was performed directly within the EwE software, using the network analysis plugin (Christensen and Walters, 2004). Thus, for the two models, the Total System Throughput (Latham, 2006), the System Omnivory Index (SOI) Libralato, 2008), the Finn's Cycling Index (FCI, Finn, 1980) and the Ascendency (A, Ulanowicz, 1997) were retained.

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In addition, the trophic level (TL), which identifies the species position within food webs, were also estimated for each functional groups according to the following equation (the routine assigns trophic level 1 to producers and a trophic level of 1+ the weighted average of the prey's trophic level to consumers):

$$TL_j = 1 + \sum_{i=1}^{N} DC_{ji}TL_j$$

where DC<sub>ji</sub> is the fraction of the prey i in the diet of the predator j.

Finally, the Detritivory/Herbivory ratio (D/H) which is the ratio between values of detritivory flows (from detritus to trophic level 2) and herbivory flows (from primary producers to trophic level 2) was calculated as proposed in Ulanowicz and Puccia (1990).

## 3. Results

The pedigree indices of the two models were 0.5 which ranks within the relatively high values when compared with 50 other models whose pedigree values ranged between 0.164 and 0.676 (Coll et al., 2006). Thus, the models seem reliable about input data of good quality.

### 3.1. Biotic indices

Concerning the macrofauna, a total of 115 species were recorded in the non-impacted zone and 78 in the impacted zone, considering all surveys. The mean values of the biomass calculated by the ECOPATH model of the ten dominant benthic species differ slightly between the two zones (impacted and non-impacted zone) (Table 1). The mean values of the biomass of these ten species were higher in the non-impacted than in the impacted zone. In the two zones *Owenia fusiformis* was the dominant species in term of biomass. It was following by the bivalves: *Albra alba*, *Acanthocardia echinata* and *Spisula subtruncata* in the non-impacted zone whereas it was followed by the brittle star *Acrocnida brachiata* and the bivalves *Spisula subtruncata* and *Abra alba* in the impacted zone.

<Table 1>

Results showed that the species richness, the abundance, the biomass and the Shannon-Wiener diversity index values estimated in the non-impacted zone were significantly higher than in the impacted zone (Tables 2 and 3). On the opposite, no significant difference in the Piélou's (J') evenness values was observed between both zones (Tables 2 and 3). Regarding the AMBI index,
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which allows assessing the ecological status of the marine environment, no significant difference was observed between both zones. The low values of the AMBI index in the non-impacted (1.81) and in the impacted zone (1.61) indicated a slightly disturbed environment and a good status (Tables 2 and 3; Figure 2). Similarly, the BO2A, which is also use to assess the Ecological Quality Status (EcoQs) of soft-bottom communities, showed no significant difference between both zones. According to the BO2A values < 0.025, the two zones could be classified as having a good ecological status (Tables 2, 3 and 4).

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<Table 2>

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<Table 3>

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<Figure 2>

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<Table 4>

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A total of 26 fish species were recorded in the non-impacted zone and 30 in the impacted zone. The biomass of the ten dominant fish species differed slightly between the two zones (impacted and non-impacted zone) (Table 5). In the two zones, the flat fish *Pleuronectes platessa* and the pouting *Trisopterus luscus* were the dominant species in term of biomass. They were following by the flat fish *Limanda limanda* and *Solea solea* in the non-impacted zone whereas it was followed by *Solea solea* and the dragonet *Callionymus lyra* in the impacted zone.

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Finally, no significant difference in fish biomass and abundance were found between the two zones (Tables 2 and 3).

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<Table 5>

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## 3.2. Functional group biomass profiles and Trophic levels

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Results showed that the total living biomass is higher in the non-impacted than in the impacted zone (Table 6). In fact, the biomass increases by approximately 31% between the non-impacted zone and the impacted zone. This increase is mostly due to the biomass increase of some compartments such as: benthic invertebrates filter feeders, selective deposit and omnivorous, which show an increase by a factor of approximately 2.45, 2 and 1.44 between the non-impacted and the impacted zone.

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Results showed that in the non-impacted zone, the benthic invertebrates selective deposit feeders was the dominant functional group in the biomass, representing approximately 30% of the total living biomass of the system. This group is mostly composed of the polychaete *Owenia*

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379 *fusiformis*. The two other groups dominating the biomass in the non-impacted zone are the
380 phytoplankton and the benthic invertebrates filter feeders (mostly composed of the bivalves *Pecten*
381 *maximus* and *Acanthocardia echinata*) making up around 24 and 20% of the total living biomass
382 (Table 6).

383 By contrast, in the impacted zone biomass was dominated by the phytoplankton and the
384 benthic invertebrates, selective deposit feeders (mostly composed of *Owenia fusiformis*)
385 representing approximately 32% and 26% of the total living biomass respectively, followed by the
386 benthic invertebrates, filter feeders and the bacteria (Table 6).

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388 <Table 6>

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390 Concerning the trophic levels, results showed that it varied from 1.0 for primary producers
391 and detritus to a maximum of approximately 4.40 represented by the functional group fish
392 piscivorous in the two zones (Figure 3; Table 6). In addition, whatever the zones, the demersal fish
393 and the cephalopods ranked just below.

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395 <Figure 3>

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397 3.3. *ENA indices*

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399 ENA results showed that the total ecosystem activity (T..) and Ascendency (A) were higher in
400 the non-impacted zone than in the impacted zone as they increased by approximately 1.57%, 4%
401 respectively between the two zones (Table 7). The System Omnivory Index SOI and the FCI remained
402 stable between both zones (Table 7). In terms of flow analysis, the results indicated that the
403 detritivory/herbivory ratio (D/H) was higher in the non-impacted (1.42) than in the impacted zone
404 (1.32). In fact, it increases by approximately 7% between the impacted and the non-impacted zone
405 (Table 7).

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407 <Table 7>

408

409 **4. Discussion**

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411 **4.1. Biotic indices**

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Relative significant differences were observed in the species richness, abundance and diversity between the impacted and the non-impacted zone with lower values observed in the impacted zone indicating a local perturbation.

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These results are consistent with the results of Pezy et al. (2018) who also found significant difference in these indices between the impacted and the non-impacted zone of the experimental Machu dumping site in the eastern part of the bay of Seine (Figure 1). However, benthic indices AMBI and BO2A as well as the Piélou's (J') evenness did not allow to do a clear distinction between the impacted and the non-impacted zone. This low difference observed between impacted and non-impacted zones with both biotic indices such as AMBI and BO2A could be explain by the difficulty of selecting non-impacted stations, with the same physical and biological characteristics as the impacted stations (to be comparable to each other), without any influence of the sediment disposal. The AMBI and BO2A indexes did not access specifically the response of the macrobenthos to bottom perturbations and the impact of sediment disposal. These indexes were more efficient to detect the response of benthic communities to the increase of organic matter (Ware et al., 2009; Munari and Mistri, 2014). To our knowledge, so far only few indicators had been specifically designed to identify the impact of dredge sediment disposal. In 1998, Roberts et al. proposed a Macrofauna Monitoring Index based on the selection of species in response to spoil disposal and calculating a ratio between the abundance of each species at impacted and unimpacted stations. The Robert's index was then modified by Dauvin et al. (2018) to the Dredge Spoil Disposal (DSD) index, which takes into account a more objective method for selecting and scoring benthic species. In the recent work, Baux et al. (2020) proposed a new index (the D²SI, for Dredge Disposal Sediment Index) which integrated several parameters (presence and abundance of benthic macrofauna and fish, bathymetry, sedimentary type and biological trait of life) to assess the impact of dumping on biological compartments and taking into account the physical changes generated by the impact of dredge sediment disposal. This index was developed with the School Case of the Machu dumping site which perfected a BACI approach (Pezy et al., 2017, 2018). The development of this type of multicriteria index is promising to highlight a specific impact on sea bottom and it would be interesting in the future to compare the D²SI response with the ENA results.

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## 4.2. *The overlooked Impact on the entire ecosystem structure and comparison with other models*

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The Total ecosystem activity (T..), system Omnivory index (SOI), Ascendency (A) and Carbon recycling (FCI) showed small variations between the impacted and the non-impacted zones of the Octeville site. This result could be explained by the fact that the Bay of Seine is historically

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characterized by a high level of human activities (Dauvin, 2006) which had led to an increase in
resilience through time to face these multiple pressures (Pezy et al., 2017).

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These ENA results from the Octeville model impacted and non-impacted zone can be
compared with other ecosystems studied with the same methodology (Ecopath) and located in the
same biome such as the model developed by Pezy et al. (2017, 2018; Table 8). The comparison
between these models revealed that highest values of the Total system activity (T..) and Ascendency
(A) were observed at the Octeville site. These results could be explained by the fact that the Octeville
models presented the highest total living biomass in comparison to the Machu models. For instance,
the non-impacted zone of the Octeville site presented a total living biomass of 33.38 gC.m⁻².year⁻¹
whereas the non-impacted zone of the Machu site at the Mabio station presented a total living
biomass of 13.96 gC.m⁻².year⁻¹ (Table 8). In addition, the results also highlighted that the highest
values of FCI (percentage of flows generated by cycling) were also found at the Octeville site. This
result could be explained by the bivalve biomass variability observed among these different models
with the highest values of FCI correlated with the highest bivalve biomass value. In fact, in their
simulation Raoux et al. (2017) highlighted a strong recycling activity linked to a high biomass of
bivalves (*Mytilus edulis*) on the wind turbine of a future Offshore Wind Farm in the Bay of Seine.

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Since Ecopath is a single solution model, it is not possible to know if these differences in FCI values
were significant. However, the FCI values of the Octeville sites could be considered as an
intermediate value when compared with the distribution of indices for pre-existing model of coastal
ecosystems (13-48%; Leguerrier et al., 2007). Concerning the system Omnivory index (SOI), these
different models presented high value of SOI, indicating that the food web of these ecosystems were
associated with a more web-like structure (Libralato, 2008). In fact, the Omnivory increased the
trophic web complexity and represented a complexity measure of the ecological network. It was
worth to note that the SOI and FCI had been described as relevant indicators of stress (Lobry et al.,
2008; Odum 1985; Scharler and Baird, 2005). On one hand, Omnivory gave flexibility to the system;
more omnivorous systems were able to absorb perturbations and to recover quicker after them
(Fagan, 1997; Libralato, 2008). On the other hand, increase in recycling was usually interpreted as a
response to stress (Odum, 1985; Scharler and Baird, 2005; Tecchio et al., 2015; Pezy et al., 2018). In
their study, Pezy et al. (2018) had highlighted an increase in FCI and SOI values as a response of stress
after dumping operations in the influenced zone of Machu on Mabio station (1 million m³ dumped in
four deposition phases of 250,000 m³, each lasting three months). Thus, the levels of both
anthropogenic and natural stress of ecosystems on the ecosystem functioning was captured by the
ENA indices (Safi et al., 2019). However, in our study no changes in FCI and SOI values were observed
between the non-impacted and the impacted zone, which were in line with the AMBI and BO2A
results suggesting that the dumping operations had a relatively limited impact on the structure and
flow pattern of the local trophic web. As mentioned, these results could be explained by the fact that this ecosystem was subject to regular natural physical and anthropogenic perturbations (Dauvin, 2006) and by its high resilience (Pezy et al., 2018; Baux, 2018). Moreover, Baux et al. (2019) highlighted a spatially relative limited impact when studying the fine particles dynamics of the Octeville dumping site. The high energy level presents on this study site allows the dispersion of the main part of dumped sediment to offshore.

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489 <Table 8>

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491 4.3. Octeville dumping site a particular environment

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The dumping site seafloor is covered with muddy sand and sandy mud in the northern and western part of the site and with gravel and pebble in the southeast part (Baux et al., 2019). The sediment of this silty heterogeneous zone corresponds to the *Abra alba* muddy-fine sand community (Baffreau et al., 2017; Baux, 2018). This community is characterised by high species richness but it is dominated by approximately ten species (with a benthopelagic life-cycle) in terms of biomass or densities (Thiébaut et al., 1997; Dauvin et al., 2017). In addition, this community is known to be characterized by very important biomasses and among the highest in Europe for the same community type (Dauvin and Desroy 2005). Maximal biomass levels of the *Abra alba* community of the eastern part of the Bay of Seine were high (annual mean 50 g DW m⁻²; maximum >200 g DW m²). Except for the very high biomass observed at the Gravelines site (southern Bight of the North Sea) just after the implantation of the invasive bivalve species *Ensis leei* M. Huber, 2015, the mean biomass observed for this community is 5–10 times higher than values generally recorded in the North Sea and the English Channel (Dauvin and Desroy, 2005).

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Thiébaut et al. (1997) qualified this community as persistent, which means that “species are able to fluctuate in abundance but, by means of adjustment of densities, a stable pattern holds” (Connel and Sousà, 1983). However, the siltation of this zone generated by both, the river flow rate activity during the last three decades (Lesourd et al., 2016), and the seventy years of dumping operations have led to the recent installation of *Melinna palmata* sandy mud community which is a muddy facies of the *Abra alba* muddy fine sand community (Baffreau et al., 2017). This new facies is also characterized by several benthopelagic lifecycle species with massive recruitment capacities and a high resilience.

As the non-impacted zone and the impacted zone have been influenced by a siltation with the installation of a new facies composed of resilient species, the following question remains:
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seventy years after the beginning of the dumping operations, is it possible to distinguish the impacted zone from the non-impacted zone?

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Our results indicate that seventy years of dumping operations have a local and relatively limited effect on the Octeville system. This high resilience of benthic community on the Octeville dumping site can be explained by the particular environment of the Eastern Bay of Seine: (1) the regular natural physical perturbations high hydrodynamic with fine-grained sediment and siltation, (2) the input of the fine particles from the Seine river combined with the input from the navigational channel and harbour basins, (3) anthropogenic pressures such as industrial and urban activities of both two Le Havre and Rouen and (4) input of several pollutants coming from the upstream part of the watershed of the Seine (Dauvin, 2006). Such estuarine pressures are common in European estuaries such as this of the Ems (de Jonge and Schückel, 2019). This estuary was divided in three upstream downstream parts Lower Reaches, Middle Reaches and Dollar, and the effects of the dredging and organic waste on the functioning and the quantitative biomass structure was explored at long-term changes from 1955, 1975 to 2005 (de Jonge and Schückel, 2019). Biomasses decreased dramatically in the three spatial compartments and the ratio between detritivory and herbivory and carbon cycling increased mainly in the Lower reaches. In a previous paper, Tecchio et al. (2015) integrated ecological data from the years 1996 to 2002 with an Ecopath with Ecosim (EwE) approach in the eastern part of the Seine estuary. The trophic flows were considered in six spatial compartments leading to six distinct EwE models: the navigation channel and the two North and South channels in the estuary proper, and three marine habitats including the mouth of the estuary in which the Octeville dumping site was located. Results showed that two habitats the North and Navigational channels showed a stressed state; they corresponded to compartments with numerous building works (North Channel) and constant continuous maritime traffic (Navigational Channel) (Tecchio et al., 2015, for more details about the habitats (north and Navigational Channel) see Tecchio et al., 2015). These results for the Ems and Seine estuaries (de Jonge and Schückel, 2019; Tecchio et al., 2015) exhibited that such modelling approach must be apprehended at a local scale more than to the entire estuary to identify effects of human pressures in such complex estuarine ecosystem.

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In addition, as the site is located in the *Abra alba* muddy fine sand community resilient community (Thiebaut et al., 1977; Dauvin et al., 2017), there is a high rapid process of colonisation of this community after a perturbation as most of the dominant species possess a benthо-pelagic cycle with massive recruitment capacities. Moreover, drifting of benthic species near the sea bottom due to a tidal transport during the flood (Olivier et al., 1996) ensured a rapid colonisation by juveniles and adults in a perturbed area such as on the Machu experimental dumping site where *Abra alba* adult (> 10 mm) were observed only three months after a deposit operation (Marmin, 2013).
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All those features make up the Octeville dumping site a particular environment under Seine estuary and long-term anthropogenic pressure, which had probably selected the more resistant benthic species along the time and was able to tolerate permanent stress due to continuous dredging deposit operation.

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Although, the data biomass of the main compartments were obtained from local, highly replicated, and detailed samplings, the data biomass of some compartments were taken from the literature and so the model results should be taken with precaution. However, pedigree values indicated that the input data used in the models were of good quality as these values were obtained from the literature for a similar sediment habitat in the eastern part of the Bay of Seine.

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Nevertheless, the dumping strategy of the Havre harbour had evolved over time to minimize impact in the Octeville zone (Baux et al., 2019). Nowadays, deposit sediments were dumped according to a system of “boxes”, in which the sediment was distributed in a thin layer (elevation of between 0.1 and 0.6m per box per year) to avoid brutal asphyxiation of benthic macrofauna (Baux et al., 2019). In the eastern part of the Bay of Seine, where important yearly dredging deposits (6-7 million m³ per year) mainly from both international harbours Rouen and Le Havre, a collaborative tripartite authority approach between National Government-Rouen and Le Havre harbours-Scientific Committee was initiated at the beginning of the 2000' towards an ecosystem approach for managing waste at the scale of the whole ecosystem of the estuary and eastern part of the bay of Seine (Marmin et al., 2014). The new Machu site for the Rouen harbour dredging deposit outside the North Channel of the Seine estuary and system of boxes with thin layer deposit in each box had also contributed to reduce the impact of these dumping zones on this shallow coastal resilient ecosystem where the impact remained local. However, it was easier to manage an estuary under one country authority, than others such as the Ems estuary without international political collaboration between the Netherlands and Germany to a single integral approach for assessment and management (de Jonge and Schückel, 2019). Similar difficulties were also underline to the management of the Scheldt estuary between the Netherlands and Belgium authorities (Meire et al., 2005). The management of dredging deposit will be simple in the future with the fusion of the La Havre and Rouen harbours with Paris harbour in a single harbour authority HAROPA (Havre-ROuen-PAris). As requested by the scientific community, a global plan of management of the Seine estuary should be a guarantee to an integral approach to assess and manage this complex ecosystem while a sectorial (spatial, human activities and natural heritage) approach was nowadays privileged (Dauvin, 2011).

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Development of new multicriteria index such as D²SI (Dredge Disposal Sediment Index) will be also useful to assess the real impact of dumping of dredge sediment disposal, jointly to take into account physical and biological perturbations and to help the harbours authorities to reduce their anthropogenic imprinted on the coastal marine ecosystems (Baux et al., 2020).

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588 Acknowledgements

589 The results in this study come from the Ph.D. thesis of N. Baux. The authors are grateful to
590 the Grand Port Maritime du Havre (GPMH, Terre Plein de la Barre, La Havre, FRANCE) for financing
591 the CIFRE thesis (CIFRE Convention N° 2015/0448), as well as data sharing and the provision of a
592 research vessel. We wish to thank the crews of "Le Marais" and "N.O. Côtes de la Manche" for their
593 help during sampling. We wish to thank the staff of the M2C Laboratory (particularly M. Legrain, C.
594 Thouroude and C. Brunaud) and the staff of CNAM-Intechmer laboratory, for assistance in technical
595 operations.

596

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809 **Figure captions**

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811 **Figure 1.** Map of the eastern part of the Bay of Seine with the location of the Machu (MASED and MABIO experimental zones) dumping site used by the harbour of Rouen since 2017 and the location of the Octeville dumping site used by the harbour of Le Havre since 1947 with focus on the two sampling zones (non-impacted and impacted zones).

815

816 **Figure 2.** AMBI index mean values in the six stations: R23, R21, R43 in the non-impacted (n=18) and GJ, IJ, HK in the impacted zone (n=18) with the percentage of the species classified in the five ecological group (I to V) defined by Borja et al. (2000) and Muxika et al. (2005). The environmental classification associated with the five EcoQs (ECological Quality Status) classes recommended by the WFD (Water Framework Directive) are used ("high"= unpolluted sites or normal; "good"= slightly polluted sites; "moderate"= Moderately polluted sites; "poor"= heavily polluted sites and "bad" for extremely polluted and azoic sites; Borja et al.,2004; Muxika et al.,2007).

823

824 **Figure 3.** Flows and biomasses of the ecosystem in the non-impacted zone.
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826

827

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<caption>**Table 1.** Mean biomass (gC. m⁻²) of the ten dominant benthic species present in the two zones (non-impacted and impacted; n= 18 for each zone) of the study area. Filter Feeders: FF, O/Scv: Omnivorous/scavengers, sDF: selective deposit feeders; nsDF: non-selectif Deposit-Feeder; P: predators.</caption>

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<table><thead><tr><th>Functional group</th><th>Non-impacted</th><th>Functional group</th><th>Impacted</th></tr></thead><tbody><tr><td>sDF</td><td>Owenia fusiformis (Annelida, Polychaeta)</td><td>sDF</td><td>Owenia fusiformis (Annelida, Polychaeta)</td></tr><tr><td>sDF</td><td>Abra alba (Mollusca, Bivalvia)</td><td>sDF</td><td>Acrocnida brachiate (Echinodermata, Ophiuridae)</td></tr><tr><td>FF</td><td>Acanthocardia echinata (Mollusca, Bivalvia)</td><td>FF</td><td>Spisula subtruncata (Mollusca, Bivalvia)</td></tr><tr><td>FF</td><td>Spisula subtruncata (Mollusca, Bivalvia)</td><td>sDF</td><td>Abra alba (Mollusca, Bivalvia)</td></tr><tr><td>sDF</td><td>Acrocnida brachiata (Echinodermata, Ophiuridae)</td><td>nsDF</td><td>Echinocardium cordatum (Echinodermata, Echinoidea)</td></tr><tr><td>FF</td><td>Phaxas pellucidus (Mollusca, Bivalvia)</td><td>nsDF</td><td>Lagis koreni (Annelida, Polychaeta)</td></tr><tr><td>O/Scv</td><td>Liocarcinus depurator (Arthropoda, Malacostraca)</td><td>sDF</td><td>Melinna palmata (Annelida, Polychaeta)</td></tr><tr><td>O/Scv</td><td>Ophiura ophiura (Echinodermata, Ophiuridae)</td><td>O/Scv</td><td>Ophiura ophiura (Echinodermata, Ophiuridae)</td></tr><tr><td>sDF</td><td>Melinna palmate (Annelida, Polychaeta)</td><td>FF</td><td>Phaxas pellucidus (Mollusca, Bivalvia)</td></tr><tr><td>nsDF</td><td>Lagis koreni (Annelida, Polychaeta)</td><td>P</td><td>Nephtys hombergi (Annelida, Polychaeta)</td></tr></tbody></table>

830

831
**Table 2.** Main characteristics of macrofauna and fishes, with different univariate indices and Standard Deviation (SD) in the non-impacted and impacted zone. S: Species richness; A: Abundance (ind. m⁻²); B: Biomass (g AFDW. m⁻²); H': Shannon-Wiener diversity index; J': Piélou's evenness index; AMBI values; BO2A values. The values of A, B, H', J', AMBI and BO2A correspond to the mean of stations per zone sampled on six dates (for macrofauna, n= 18 on impacted zone and non-impacted zone respectively. For fish, n= 16 on impacted zone and n= 24 on non-impacted zone). Significant difference (p-value < 0.05) are indicated by a letter (a, b).

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<table><thead><tr><th rowspan="2"></th><th rowspan="2"></th><th colspan="2">Non-impacted</th><th colspan="2">Impacted</th></tr><tr><th>Mean values</th><th>SD</th><th>Mean values</th><th>SD</th></tr></thead><tbody><tr><td rowspan="7">Macrofauna</td><td>S</td><td>48<sup>a</sup></td><td>±6.67</td><td>30<sup>b</sup></td><td>±8.49</td></tr><tr><td>A</td><td>3,128<sup>a</sup></td><td>±1,620.25</td><td>1,704<sup>b</sup></td><td>±986.44</td></tr><tr><td>B</td><td>23.66<sup>a</sup></td><td>±15.39</td><td>13.95<sup>b</sup></td><td>±88.88</td></tr><tr><td>H'</td><td>3.95<sup>a</sup></td><td>±0.33</td><td>3.44<sup>b</sup></td><td>±0.42</td></tr><tr><td>J'</td><td>0.71</td><td>±0.06</td><td>0.71</td><td>±0.08</td></tr><tr><td>AMBI</td><td>1.61</td><td>±0.31</td><td>1.81</td><td>±0.36</td></tr><tr><td>BO2A</td><td>0.03</td><td>±0.02</td><td>0.03</td><td>±0.03</td></tr><tr><td rowspan="2">Fish</td><td>A</td><td>0.04<sup>a</sup></td><td>±0.01</td><td>0.02<sup>b</sup></td><td>±0.01</td></tr><tr><td>B</td><td>1.75<sup>a</sup></td><td>±0.28</td><td>2.37<sup>b</sup></td><td>±0.93</td></tr></tbody></table>

840

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**Table 3.** Results of the non-parametric Kruskal-Wallis test on seven parameters between the non-impacted and the impacted zones. S: Species richness; A: Abundance (ind. m⁻²); B: Biomass (g AFDW. m⁻²); J': Piélou's evenness index; H': Shannon-Wiener diversity index; AMBI values; BO2A values; Df: Degrees of Freedom; F: F-ratio score; I: Impacted zone; NI: Non-Impacted zone. For macrofauna, n= 18 on impacted zone and non-impacted zone respectively. For fish, n= 16 on impacted zone and n= 24 on non-impacted zone).

<table><thead><tr><th></th><th></th><th>Df</th><th>F</th><th>P-value</th><th>Interpretation</th></tr></thead><tbody><tr><td rowspan="7">Macrofauna</td><td>S</td><td>1</td><td>20.797</td><td>&lt; 0.001</td><td>I ≠ NI</td></tr><tr><td>A</td><td>1</td><td>8.567</td><td>0.003423</td><td>I ≠ NI</td></tr><tr><td>B</td><td>1</td><td>4.2292</td><td>0.03973</td><td>I ≠ NI</td></tr><tr><td>J'</td><td>1</td><td>0.01616</td><td>0.8993</td><td>I = NI</td></tr><tr><td>H'</td><td>1</td><td>11.893</td><td>&lt; 0.001</td><td>I ≠ NI</td></tr><tr><td>AMBI</td><td>1</td><td>3.4845</td><td>0.06195</td><td>I = NI</td></tr><tr><td>BO2A</td><td>1</td><td>0.036041</td><td>0.8494</td><td>I = NI</td></tr><tr><td rowspan="2">Fish</td><td>A</td><td>1</td><td>24.259</td><td>&lt; 0.001</td><td>I ≠ NI</td></tr><tr><td>B</td><td>1</td><td>23.2</td><td>&lt; 0.001</td><td>I ≠ NI</td></tr></tbody></table>

848

849
Table 4. BO2A index mean values in the six stations: R23, R21, R43 in the non-impacted and GJ, IJ, HK in the impacted zone. Classification used come from Dauvin et al. (2016); Dauvin (2018).

852

<table><thead><tr><td>Stations</td><td>BO2A values</td><td>EcoQs</td><td>SD</td></tr></thead><tbody><tr><td>GJ</td><td>0.02241</td><td>High</td><td>0.021</td></tr><tr><td>HK</td><td>0.03569</td><td>Good</td><td>0.031</td></tr><tr><td>IJ</td><td>0.03039</td><td>Good</td><td>0.028</td></tr><tr><td>R21</td><td>0.02364</td><td>High</td><td>0.007</td></tr><tr><td>R23</td><td>0.01533</td><td>High</td><td>0.007</td></tr><tr><td>R43</td><td>0.03705</td><td>Good</td><td>0.028</td></tr></tbody></table>

853
Table 5. Mean biomass (gC. m⁻²) of the ten dominant fish species present in the two zones (non-impacted and impacted. n= 18 for each zone) of the study area.

<table><thead><tr><th>Functional group</th><th>Non-impacted</th><th>Functional group</th><th>Impacted</th></tr></thead><tbody><tr><td>Benthos feeders</td><td>Pleuronectes platessa</td><td>Benthos feeders</td><td>Pleuronectes platessa</td></tr><tr><td>Demersal</td><td>Trisopterus luscus</td><td>Demersal</td><td>Trisopterus luscus</td></tr><tr><td>Benthos feeders</td><td>Limanda limanda</td><td>Benthos feeders</td><td>Solea solea</td></tr><tr><td>Benthos feeders</td><td>Solea solea</td><td>Benthos feeders</td><td>Callionymus lyra</td></tr><tr><td>Benthos feeders</td><td>Callionymus lyra</td><td>Benthos feeders</td><td>Limanda limanda</td></tr><tr><td>Demersal</td><td>Raja clavata</td><td>Piscivorous</td><td>Conger conger</td></tr><tr><td>Benthos feeders</td><td>Scyliorhinus canicula</td><td>Demersal</td><td>Merlangius merlangus</td></tr><tr><td>Piscivorous</td><td>Conger conger</td><td>Benthos feeders</td><td>Buglossidium luteum</td></tr><tr><td>Demersal</td><td>Merlangius merlangus</td><td>Demersal</td><td>Trisopterus minutus</td></tr><tr><td>Benthos feeders</td><td>Buglossidium luteum</td><td>Benthos feeders</td><td>Platichthys flesus</td></tr></tbody></table>
858 **Table 6.** Biomass and trophic level values for the two models (non-impacted and impacted zones).

859 O/Scv: Omnivorous/scavengers, P: predator, Filter Feeders: FF, sDF: selective deposit feeders, nsDF

860 non-selective deposit feeders.

<table><thead><tr><th rowspan="2"></th><th colspan="2">Biomass gC.m<sup>2</sup></th><th colspan="2">TL</th></tr><tr><th>Non-impacted</th><th>Impacted</th><th>Non-impacted</th><th>Impacted</th></tr></thead><tbody><tr><td>Cephalopods</td><td>0.00014</td><td>0.00013</td><td>3.90</td><td>3.90</td></tr><tr><td>Fish piscivorous</td><td>0.004</td><td>0.007</td><td>4.40</td><td>4.38</td></tr><tr><td>Fish demersal</td><td>0.045</td><td>0.058</td><td>4.04</td><td>4.03</td></tr><tr><td>Fish benthic feeders</td><td>0.298</td><td>0.267</td><td>3.34</td><td>3.33</td></tr><tr><td>Fish planktivorous</td><td>0.00521</td><td>0.00836</td><td>3.15</td><td>3.15</td></tr><tr><td>Benthic invertebrates, O/Scv</td><td>1.480</td><td>0.724</td><td>3.06</td><td>3.04</td></tr><tr><td>Benthic invertebrate, P</td><td>1.324</td><td>1.019</td><td>3.19</td><td>3.19</td></tr><tr><td>Benthic invertebrates, FF</td><td>6.690</td><td>2.733</td><td>2.27</td><td>2.27</td></tr><tr><td>Benthic invertebrates, sDF</td><td>9.550</td><td>6.617</td><td>2.22</td><td>2.21</td></tr><tr><td>Benthic invertebrates, nsDF</td><td>0.923</td><td>1.008</td><td>2.22</td><td>2.22</td></tr><tr><td>Meiofauna</td><td>0.377</td><td>0.377</td><td>2.26</td><td>2.26</td></tr><tr><td>Zooplankton</td><td>1.715</td><td>1.715</td><td>2.15</td><td>2.15</td></tr><tr><td>Bacteria</td><td>2.800</td><td>2.800</td><td>2.00</td><td>2.00</td></tr><tr><td>Phytoplankton</td><td>8.170</td><td>8.170</td><td>1.00</td><td>1.00</td></tr><tr><td>Detritus</td><td>9.050</td><td>9.050</td><td>1.00</td><td>1.00</td></tr></tbody></table>

861

862
**Table 7.** ENA indices for the two models (non-impacted and impacted zones). The Total System Throughput (T.. gC m⁻² year⁻¹) is calculated as the sum of all flows in the food web. FCI gives the percentage of all flows generated by cycling. The Ascendency (A) is a measure of the system activity (Total System Throughput) linked to its degree of organization (AMI) and is expressed in gC m⁻² year⁻¹. The SOI is a proxy of the trophic web complexity.

<table><thead><tr><th>ENA</th><th>Non-impacted</th><th>Impacted</th></tr></thead><tbody><tr><td>T..</td><td>2013.00</td><td>1982.00</td></tr><tr><td>A</td><td>2308.00</td><td>2219.00</td></tr><tr><td>FCI</td><td>23.00</td><td>23.00</td></tr><tr><td>SOI</td><td>0.20</td><td>0.20</td></tr><tr><td>D/H</td><td>1.42</td><td>1.32</td></tr></tbody></table>
**Table 8.** General system statistics and ENA indices for the Octeville models compared to values obtained for similar systems also influenced by dumping operations in the estuary and Bay of Seine. The Total System Throughput (T.. gCm-2 year-1) is calculated as the sum of all flows in the food web. The Ascendency (A) is a measure of the system activity (Total System Throughput) linked to its degree of organization (Average Mutual Information) and is expressed in gCm-2 year-1. Finn's Cycling Index (FCI) gives the percentage of all flows generated by recycling. The System Omnivory Index (SOI) is calculated as the average of the OIs of the individual group weighted by the logarithm of each consumer intake.

<table><thead><tr><th>Ecosystems</th><th></th><th>T..</th><th>A</th><th>FCI</th><th>SOI</th><th>Total Biomass</th><th>Reference</th></tr></thead><tbody><tr><td rowspan="3">Machu<br>(MABIO)</td><td>Before</td><td>1130</td><td>1130</td><td>12%</td><td>22</td><td>20.71</td><td rowspan="3">Pezy et al., 2017</td></tr><tr><td>After</td><td>1144</td><td>1138</td><td>10%</td><td>25</td><td>22.36</td></tr><tr><td>Non-impacted zone</td><td>982</td><td>1089</td><td>9%</td><td>24</td><td>13.96</td></tr><tr><td rowspan="2">Machu<br>(MABIO)</td><td>Influenced zone</td><td>1194</td><td>1170</td><td>13%</td><td>21</td><td>21.76</td><td rowspan="2">Pezy et al., 2018</td></tr><tr><td>Impacted zone</td><td>949</td><td>1061</td><td>9%</td><td>23</td><td>13.41</td></tr><tr><td rowspan="2">Octeville</td><td>Non-impacted zone</td><td>2013</td><td>2308</td><td>23%</td><td>20</td><td>33.38</td><td rowspan="2">This study</td></tr><tr><td>Impacted zone</td><td>1982</td><td>2219</td><td>23%</td><td>20</td><td>25.50</td></tr></tbody></table>

880

881
<figure><img src="image_3.png" /><figcaption>882 Figure 1.</figcaption></figure>

883

884
<figure><img src="image_4.png" /><figcaption>Figure 2.</figcaption></figure>
<figure><img src="image_5.png" /><figcaption>Figure 3.</figcaption></figure>