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Title: Relating macroinvertebrate community structure to environmental characteristics and

sediment contamination at the scale of the St. Lawrence River

Article Type: SI: St. Lawrence 50 year overview

Keywords: macroinvertebrates, St. Lawrence River, community structure, sediment contamination,

environmental characteristics, indicator taxa

Corresponding Author: Stephane Masson,

Corresponding Author's Institution:

First Author: Stephane Masson

Order of Authors: Stephane Masson; Mélanie Desrosiers; Bernadette Pinel-Alloul; Louis Martel

1

Relating macroinvertebrate community structure to environmental characteristics 1

and sediment contamination at the scale of the St. Lawrence River2

3

4

Stéphane Masson1*, Mélanie Desrosiers23, Bernadette Pinel-Alloul2, & Louis Martel35

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1Aquarium du Québec, SÉPAQ, 1675 av. des Hôtels, Québec, QC, Canada, G1W 4S37

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2GRIL, Département de Sciences Biologiques, Université de Montréal, C.P. 6128, Succ Centre-Ville, 9

Montréal, Québec, Canada, H3C 3J710

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3CEAEQ, Ministère du Développement durable de l’Environnement et des Parcs du Québec, 2700 rue 12

Einstein, Québec, Canada, GIP 3W813

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Key words: macroinvertebrates, St. Lawrence River, community structure, sediment contamination,15

environmental characteristics, indicator taxa16

17

*Corresponding author: Stéphane Masson18

Aquarium du Québec, SÉPAQ, 1675 av. des Hôtels, Québec, QC, Canada, G1W 4S3. 19

email : masson.stephane@sepaq.com20

21

This paper has not been submitted elsewhere in identical or similar form nor will it be during the first 22

three months after its submission to Hydrobiologia23

ManuscriptClick here to download Manuscript: Hydrobiol Masson et al VF.doc Click here to view linked References

2

Abstract24

The St. Lawrence River is one of the most important rivers in the world located in the most populous 25

region of eastern Canada and subjected to multiple stressors induced by human activities. There is still 26

no assessment of the impact of sediment chemicals and environmental conditions on macroinvertebrate 27

community at the scale of the St. Lawrence River continuum. This study aims to characterize the 28

community structure of macroinvertebrates in the fluvial section of the St. Lawrence River including 29

the three fluvial lakes and the Montreal harbour using several taxonomic levels (genus and family) and 30

data (abundance, presence/absence and indicator taxa). The goal of the study is to relate changes in 31

macroinvertebrate community to sediment chemical conditions and environmental characteristics of 32

habitats. A special effort was made for identifying indicator taxa characteristic of the different 33

macroinvertebrate assemblages along the river fluvial continuum. Furthermore, this study also aims to34

determine the taxonomic level and the data suitable for a good assessment of the relative contribution 35

of sediment chemical conditions and environmental characteristics of habitats using variance 36

partitioning. Four different macroinvertebrate assemblages were found distributed along environmental 37

gradients in the fluvial continuum both when using abundance or presence/absence data at the genus 38

and family levels. Specific indicator taxa were characteristics of the different macroinvertebrate 39

communities and were associated to the contamination gradient. Environmental characteristics of the 40

habitats (water masses, sulphur and DOC in sediments) had higher influence on macroinvertebrate 41

assemblages than sediment chemical conditions, with strong interactive effects. However together they 42

explain less than 30% of the total variance in macroinvertebrate communities. Our study confirms that 43

family level can give comparable information than genus level using presence-absence or abundance 44

of macroinvertebrates, however, higher number of indicator taxa were detected at the genus level.45

46

47

3

Introduction48

49

The St. Lawrence River is one of the most important large rivers in the world and represents almost 50

25% of freshwater reserves in earth. It drains an area of 1 610 000 km2 and flows throughout 1000 km 51

from Lake Ontario to the Gulf of St. Lawrence in one of the most populous regions of Canada. 52

Intensive agriculture, urbanization and industrialization in its watershed and shores maintain a constant 53

pressure to this river. In the mid-1980s, the most heavily contaminated areas of the St. Lawrence River 54

were the fluvial lakes (Saint-Louis and Saint-Pierre) and the harbour areas of Montreal and Quebec 55

cities (Loiselle et al., 1997). Since the fifties, industrialization has caused the contamination of the St. 56

Lawrence River by trace metals and organic pollutants (Allen, 1986; Carignan et al., 1994). Although 57

a decline in contamination has been noted in recent years, there are still some sources of local pollution 58

from human activities such as discharges of industrial, agricultural and municipal wastewaters. Other 59

sources also contaminate the river as landfills coastal shipping, port and dredging activities, and 60

pharmaceutics contaminants.61

62

Macroinvertebrate communities have been extensively used for bioassessment of freshwater systems 63

(Hellawell, 1986; Rosenberg & Resh, 1993; Chessman et al., 2007). In the St. Lawrence River, the 64

distribution and community structure of macroinvertebrates were shown to be related to multiple 65

environmental factors including habitat vegetation, water quality, sediment grain size and 66

contamination (Cook & Johnson, 1974; Cyr & Downing, 1988; Pinel-Alloul et al., 1996). However, 67

most of these studies differ by the level of taxonomic analysis, the metrics describing 68

macroinvertebrate communities, the sampling methods, the statistical approaches, and the 69

contaminants measured (Pinel-Alloul et al., 2004). Furthermore, they are limited to specific 70

ecosystems, either one of the fluvial lakes or harbours of the river. Pinel-Alloul et al. (1996) assessed 71

4

the relative importance of environmental characteristics and sediment contamination, and of their 72

interaction, in explaining the composition and abundance of macroinvertebrate communities in Lake 73

Saint-François. It is the less polluted lake of the St-Lawrence River upward Montreal, while the main 74

sources of contamination dues to municipal effluents and extensive agriculture are located downward 75

Montreal. Tessier et al. (2008) evaluated the variation in macroinvertebrate community among three 76

vegetation types (emergent and submerged vegetation, filamentous algal mats) and water masses,77

whereas Tall et al. (2008) evaluated the potential of emergent vegetation and sediment habitats for 78

developing a bioassessment program with reference conditions using macroinvertebrates in Lake 79

Saint-Pierre only. There is still no assessment of the impact of sediment quality on macroinvertebrate 80

community at the scale of the St. Lawrence River continuum.81

82

This study establishes large scale patterns of macroinvertebrate community structure in relation to 83

sediment contamination and environmental characteristics along a 240-km continuum of the fluvial 84

section of the St. Lawrence River. It covers the full range of habitats including the three fluvial lakes 85

(Saint-François, Saint-Louis, and Saint-Pierre) and the Montreal harbour area. The goals of the study 86

are three folds: 1) to describe the geographical patterns in macroinvertebrate community structure 87

using different taxonomic levels (genus and family) and data (presence/absence or abundance), 2) to 88

determine indicator taxa of the different macroinvertebrate communities distributed along the fluvial 89

section of the St. Lawrence River, and 3) to establish the link between macroinvertebrate community 90

structure and spatial variation in the water and sediment quality along the St. Lawrence River, and 91

evaluate their relative contribution using variance partitioning. 92

93

94

95

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Materials and methods96

Study area97

98

The study area covers a 240-km long section of the fluvial continuum of the St. Lawrence River 99

(Canada) from Lake Saint-François at the outlet of Lake Ontario to the outlet of Lake Saint-Pierre 100

(Fig. 1). Sampling stations were located in sedimentation zones of the three main fluvial lakes and the 101

Montreal harbour at sites impacted by fine-particle deposition, potential dredging, and past or present 102

anthropogenic contamination point sources. A total of 59 stations were visited during fall 2004 and 103

2005. Ten stations were located in Lake Saint-François, 21 stations in Lake Saint-Louis, 15 stations in 104

Lake Saint-Pierre, 11 stations in the Montreal harbour and 2 others downstream towards Montreal 105

Island close to a major municipal wastewater dispersion plume (Fig. 1). The location of each sampling 106

station within the different water masses coming from the Great Lakes waters on the south shores and 107

from the Ottawa River on the north shores that flow along the fluvial corridor of the St. Lawrence 108

River was determined using cartographic tools (Désilets & Langlois, 1989; Nettleton, 1996).109

110

Sediment sampling and analyses111

112

Surface sediments were collected with a Shipek grab sampler (400 cm2). In each station, 20 to 25 L of 113

sediment were randomly collected in the sampling zone and placed in clear polyethylene bags. All 114

bags were placed on ice in a container during 24 - 30 hrs until their arrival at the laboratory where they 115

were stored in a cold chamber (4oC). Twenty four to 48 hours after sampling, sediment samples116

collected at each station were sieved on a 2-mm mesh sieve and manually homogenized before sub-117

sampling for each type of chemical analyses (Tables 1 and 2). Sediment pore water was extracted by 118

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two centrifugation processes: first with the entire sediment sample (3000 G; 20 min) and then after on 119

the retrieved pore water (10000 G; 30 min). Sub-samples of interstitial water were kept for measuring 120

dissolved organic carbon (DOC). 121

122

In each sediment sample, we measured the grain size, the concentrations of nutrients (Total Kjeldahl 123

Nitrogen: TKN; Total phosphorus: TP; total sulphur, total organic carbon (TOC), calcium (Ca), metals124

(Al, As, Cd, Cr, Cu, Fe, Mn, Ni, Pb, Zn, and total mercury: THg), and organic contaminants (PCBs, 125

PAHs, four pesticides groups, and petroleum hydrocarbons) (see Tables 1 and 2 for details on 126

analytical methods and detection limits). All chemical methods were based on AC/QC standardized 127

protocols developed and validated at the “Centre d'expertise en analyse environnementale du Québec”128

(CEAEQ) (see references in Tables 1 and 2). Sediment conditions varied among and within the 129

sampling areas and covered a large range of grain size, organic matter, nutrient, organic chemical, 130

metal, and metalloid concentrations with the highest chemical concentrations generally observed in the 131

Montreal harbour area (Desrosiers et al., 2008).132

133

Macroinvertebrate sampling and analyses134

135

Five samples of macroinvertebrates were randomly collected at each station using a Shipek grab (400 136

cm2) and placed into a clear polyethylene bag (food grade; 30 x 37 cm). Samples were preserved on 137

site in 10% formaldehyde solution stained with Rose Bengal to fix and colour macroinvertebrates in 138

order to reduce sorting time. Three replicates of macroinvertebrates samples were analyzed in 139

laboratory. Sediment samples were rinsed with tap water and macroinvertebrates were collected on a 140

sieve of 500 µm mesh size and sorted at coarse taxonomic level under a lighting magnifying glass. The 141

organisms were then stored in 70% glycerol-coated alcohol for later identification. In 30% of the 142

7

samples, it was necessary to carry out subsampling because of the high quantity of sediment collected. 143

In these cases, the entire sediment sample was weighted before being sieved on the 500-um mesh 144

screen and homogenized by dipping it in water in a container. Thereafter, the sample was removed 145

from the water and a fraction of it was taken, weighed to estimate the proportion (%) analysed and 146

checked for macroinvertebrates. At least 25% of the sample was retained in order to respect a 147

maximum of eight hours of time for sorting macroinvertebrates. 148

149

Taxonomic analysis of macroinvertebrates was carried out by a private firm (Laboratoires SAB inc.) at 150

the family, genera and species levels using several identification keys and methods (Klemm et al., 151

1990; Merritt & Cummins, 1996; Thorp & Covich, 2001; Environment Canada, 2005). In some 152

stations where the abundances of oligochaetes, chironomids and gastropods were very high, a 153

minimum of 100 individuals were randomly taken in the flask and identified. The frequencies of the 154

different taxa were applied to the total number. A reference collection was provided to specialised 155

taxonomists at the Université de Montréal (Québec, Canada) who validated all identifications made at 156

the genus level. 157

158

Statistical analyses159

160

To describe the spatial patterns of distribution of macroinvertebrates assemblages along the fluvial 161

continuum and identify indicator taxa, we applied multivariate statistical analyses following Dufrêne 162

and Legendre (1997). First, we performed Principal Coordinate Analysis (PCoA) to identify clusters of 163

stations presenting similarity in their macroinvertebrate communities using abundance, and 164

presence/absence data at genus and family levels. For each set of the four matrices (59 stations x 165

abundance and presence/absence of genus and families), data were normalized using the Hellinger 166

8

transformation (Legendre & Gallagher, 2001) and then used to build the similarity matrices using the 167

index distance Hellinger (D17). Secondly, a non-hierarchical clustering analysis (K-means) was168

performed to identify different clusters of stations (Legendre & Legendre, 1998). Although the simple 169

structure index (SSI) was used to determine the optimum number of clusters (e.g.: for instance, 7 170

groups represented the optimum similarity in the macroinvertebrate abundances at the genus level for 171

all stations), we looked at various possibilities for clustering (4 to 10 groups). Thirdly, we used the 172

IndVal method developed by Dufrêne and Legendre (1997) to identify indicator taxa associated to the 173

typology of macroinvertebrate assemblages obtained by PCoA clustering. This method enabled us to 174

group taxa on the basis of their indicator value (IndVal) for each clustering level (4 to 10). For each 175

taxa i in each group j, we computed the product of Aij, which is the mean abundance of taxa i in the 176

sites of group j compared to all groups, by Bij, which is the relative frequency of occurrence of taxa i177

in the sites of group j, as follows :178

Aij = N individualsij / N individualsi179

Bij = N sitesij / N sitesj180

IndValij = Aij * Bij * 100181

Where IndVal is the indicator value of taxa i in the group j. Aij is a measure of specificity of the taxa 182

in a group, while Bij is a measure of fidelity of this taxa within that group (Dufrêne & Legendre, 183

1997).184

185

Redundancy analyses (RDAs) were performed to establish a model relating macroinvertebrate 186

community to environmental characteristics and chemical contamination. RDA measured all the 187

variance of macroinvertebrate matrix in relation to chemical concentrations in sediment and 188

environmental characteristics using Monte Carlo unrestricted 999 permutation tests (Legendre & 189

Legendre, 1998). RDA analyses were performed with chemical and environmental data considered 190

9

separately or put together. Only the variables presenting significant relationships (p < 0.05) after 191

stepwise selection were kept in the final RDA model obtained using macroinvertebrate data at the 192

genus and family level. We used Hellinger transformation for the macroinvertebrate abundance matrix 193

containing many zeros, as recommended by Legendre and Gallagher (2001). Partial RDAs were 194

performed for determining the relative contribution of chemical and environmental characteristics of 195

the sediment in the model explaining variation in macroinvertebrate community structure along the 196

fluvial continuum.197

The free software environment R (version 2.6.1) was utilized for multivariate statistical computing and 198

graphics (Ihakam & Gentleman, 1996): http://www.r-project.org/). Statistical analyses were performed 199

with different R libraries: Labsbv library and Duleg function for IndVal; Vegan for K-mean, and 200

partial RDA. Finally for RDA we used Vegan and Packford libraries using forward selection with 201

permutation test (999).202

203

Results204

205

Spatial distribution, clustering and indicator taxa of macroinvertebrate communities206

207

PCoA and K-means analyses discriminated four clusters of stations (groups A to D) which showed 208

similarity in macroinvertebrate community structure based on abundances of genus and family taxa 209

(Fig. 2). These analyses were also performed to obtain various possibilities of stations clustering from 210

4 to 10 groups. Finally, we retained only the model with four groups of stations because no indicator 211

taxa were found for each group when the number of clusters of stations was more than four. At the 212

genus level (Fig. 2A), the Montreal harbour stations (group A) and the Lake Saint-François stations 213

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associated with few stations of Lake Saint-Louis and Lake Saint-Pierre (group B) formed two distinct 214

clusters located at both ends of the first axis of the ordination. The clusters C and D were only 215

composed of stations of Lake Saint-Louis and Lake Saint-Pierre. At the family level (Fig. 2B), we 216

obtained similar geographical patterns with the Montreal harbour stations and few stations of Lake 217

Saint-Louis and Lake Saint-Pierre in group A, most of the stations of Lake Saint-François stations in 218

groups B and D, and other stations of Lake Saint-Pierre and Lake Saint-Louis in group C.219

220

At the genus level, we identified two to nine indicator taxa in the four clusters (Fig. 2A). Two 221

Oligochaeta Tubificidae (IIyodrilus and Quistadrilus) were representative taxa for macroinvertebrate 222

community of the cluster A in the Montreal harbour. Nine (9) indicator taxa were characteristic of the 223

macroinvertebrate community in the cluster B; they included one Hirudinae, one Arachnida, two 224

Malacostraca, four insect larvae (three Chironomidae and one Leptoceridae) and one Planariidae. Two 225

indicator taxa (the Nemerta and the Oligochaeta Tubificidae, Spirosperma) were also identified for the 226

cluster C. Four taxa were characteristic of the cluster D, one Ephemera (Hexagenia), and three Diptera 227

chironomidae (Axarus, Ablabesmyia and Coelotanypus). At the family level, clusters A and C had no228

significant indicator taxa; cluster D had one indicator taxa (the insect larvae of Ephemeridae) and the 229

cluster B, like at the genus level, has the greatest number of indicator taxa (five families including two 230

Malacostraca, two insect larvae (Hydroptilidae, Leptoceridae) and the Planariidae) (Fig. 2B). 231

232

PCoA and K-means analyses based on presence/absence of genus and family taxa (Fig. 3) also 233

discriminated four clusters of stations (groups A to D) which showed similar distribution of 234

macroinvertebrate communities along the first axis of the ordination, like for the abundance data. 235

However, we did not find as much indicator taxa at the genus level (Fig. 3A). No indicator taxa were 236

characteristic for the clusters A and B, only one Oligochaeta Tubificidae for the cluster C and six 237

11

indicator taxa were identified for the cluster D (including one Arachnida, one Malacostraca and four 238

insect larvae: three Chironomidae and one Leptoceridae). With presence/absence data at the family 239

level (Fig. 3B), we obtained indicator taxa in three groups (A, C, D) compared to two groups (C, D) at 240

the genus level, and more indicator taxa than when using abundance data.241

242

There were also some differences and similarities in the detection of indicator taxa when using 243

abundance or presence/absence data at the genus and family levels. For instance, indicator taxa for the 244

group A were very different between analyses. Two Oligochaeta were identified when using 245

abundances at the genus level (Fig. 2A), while the Gastropoda Planorbidae and Planariidae were 246

retained when using presence/absence data at the family level (Fig. 3B).. At the opposite, no matter the 247

taxonomic level used, some common indicator taxa were identified for the group D in the four 248

analyses, such as the Gammaridae and Leptoceridae. 249

250

Influence of sediment quality and environment on macroinvertebrate communities 251

252

When using only sediment contamination by inorganic and organic chemicals, we explained a very 253

low percentage of the total variance of the indicator taxa along the fluvial continuum of the St. 254

Lawrence River (cumulative r2 from 0.10 to 0.17: Table 3). Similar results were obtained for 255

abundance or presence/absence data at the genus or family level (Table 3). The first explanatory 256

variables were Pb or Zn, while the other variables were total mercury (THg) and total PAH (PAHtot), 257

as well as As and Ni for presence/absence data at the family level (Table 3). 258

259

Higher percentages of the total variance in macroinvertebrate communities were explained when using 260

environmental characteristics alone (cumulative r2 from 0.18 to 0.25; Table 4). The significant 261

12

explanatory variables were different depending on the invertebrates community descriptor and 262

taxonomic level. Macroinvertebrate community structure at the genus level was mainly explained by 263

differences in water masses originating from the Ottawa River in the north shores and from the Great 264

Lakes in the south shores, Montreal municipal wastewater (CUM), total sulphur, DOC, sandy sediment 265

and Mn concentrations (Table 4). When using only significant indicator taxa at the genus level, 266

community structure was explained by DOC, total sulphur, % of sand and water depth. On the other 267

hand, community structure at the family level was also explained by different water masses, by the N/P 268

ratio in sediment, NH3, sulphur and DOC concentrations and by the water depth. 269

270

Highest percentage of explained variance in macroinvertebrate community structure were obtained 271

when chemical concentrations in sediments and environmental characteristics were mixed in a single 272

RDA model. Then, we explained 29% of the variance in macroinvertebrate abundances at the genus 273

level, and the significant explanatory variables were sulphur, THg, and the percentage of water in 274

sediment (humidity) along the positive end of the first axis and DOC, Pb, Zn, and HAPtot along the 275

negative end (Fig. 4A). On the first axis, the Oligocheata Limnodrilus and Quistadrilus were 276

associated to high concentrations of DOC, HAPtot, Pb and Zn located in the stations of the Montreal 277

harbour. At the opposite end of axis 1, THg gradient was related to stations located in Lake Saint-278

François and Lake Saint Louis (Fig. 4A). Two gastropods (Amnicola and Gyraulus), the amphipod 279

(Gammarus), the Trichoptera Nectopsyche and Leptocerus and the Diptera Chironomidae 280

Clinotanypus were associated to the THg contamination. A third gradient on axis 2 was associated to 281

sulphur concentrations and water percentage (humidity) in sediments. Some Diptera Chironomidae 282

(Chironomus, Dicrotendipes, Tribelos), the Gastropoda Bithynia and the Isopoda Caecidatea and 283

Lirceus were related to sediments with higher sulphur concentrations and percentage of water. On the 284

negative side of the axis 2, macroinvertebrate community were associated to the less contaminated 285

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area located in Lake Saint-Louis and Lake Saint-Pierre and were dominated by several genus of 286

Nematoda, Nemerta, Oligochaeta, Bivalva and Ephemera. 287

288

N/P ratio in sediment, Zn, sulphur, THg, high molecular weight HAPs, and the Saint-Louis River 289

water mass explained 34% of the variance in macroinvertebrate abundances at the family level (Fig. 290

4B). As for abundance data at the genus level, Oligochaeta Tubificidae dominated in stations 291

contaminated by HAPs and Zn. At the opposite side, again, we observed the gradient of THg related to 292

Saint-Louis River water mass. The Trichoptera Dipseudopsidae, the Oligochaeta Naididae and the 293

Gastropoda Hydrobiidae were associated to these variables. Along the second axis, sulphur294

concentrations and N/P ratio were related to isopod Asellidae and Gastropoda Bithyniidae. The Diptera 295

Chironomidae were associated to both THg and N/P ratio. The Nematoda inhabited the less 296

contaminated stations.297

298

Variation in macroinvertebrate community structure based on presence/absence data at the genus and 299

family levels was explained by similar variables than abundance data such as water masses (Ottawa 300

River, Great Lakes, CUM wastewater), metals or metalloids concentrations (As, Pb, Zn), DOC, total 301

sulphur, and sediment granulometry (silt) and humidity (Fig. 5A). Many Oligocheata taxa, the Porifera 302

Spongillidae Eunapius, the platyhelminthes and the Nematoda were associated to the contaminated 303

area. As observed with abundance data, sulphur concentrations were retained as an explanatory 304

variable with presence/absence data with similar genus and family indicator taxa (Crustacea, 305

Trichoptera and Diptera). Once again, a lot of species were identified in the less contaminated zones, 306

such as the Ephemera Hexagenia, the Diptera Probezzia, Cryptochironomus, Coelotanypus, 307

Ablabesmyia, the Polycheata Manayunkia, the Nemerta Prostoma and the Coleoptera Dubiraphia.308

309

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Variations in abundances of macroinvertebrate indicator genus were explained by concentrations of 310

Zn, sulphur and DOC, sand and silt percentages, and Great Lakes water mass with a cumulated r2 of 311

0.31 (Fig. 6). The most contaminated areas in the Montreal harbour and some stations in lakes Saint-312

Louis and Saint-Pierre were associated to higher concentrations in Zn and DOC and were dominated 313

by the two Oligocheata Tubificidea IIyodrilus and Quistadrilus. As previously observed for the entire 314

community, the Chironomidae Chironomus and Dicrotendipes were associated with the sulphur315

gradient. The Ephemera Hexagenia, the Nemerta and the Oligochaeta Spirosperma were located in 316

less contaminated stations of lakes Saint-Louis and Saint-Pierre.317

318

Partial redundancy analyses showed similar results with all datasets whatever the taxonomic level 319

(Fig. 7). In general, environmental characteristics related to water masses, DOC and sulphur 320

concentrations in sediments explained between 7 to 10% of macroinvertebrate community structure 321

whereas sediment contamination accounted for less that 2% of the total variance. The interactions 322

between environmental characteristics and sediment contamination also accounted for as much 323

explained variance as the environmental characteristics alone. All models showed high percentages 324

(78-84%) of unexplained variance or residuals (Fig. 7). 325

326

Discussion327

328

Macroinvertebrate assemblages and indicator taxa329

330

Our study showed that four different assemblages of macroinvertebrates were detected along the 331

fluvial section of the St. Lawrence using either abundance or presence/absence data at the genus or 332

family levels. These four types of community were characterized by indicator taxa. Macroinvertebrate 333

15

community occurring in the most contaminated areas of the Montreal harbour and some stations of the 334

Lake Saint-Louis and Lake Saint-Pierre (Cluster A) was characterized by tolerant taxa such as the 335

Oligochaeta Tubificidae (IIyodrilus and Quistadrilus). The presence of Oligochaeta Tubificidae is 336

often associated with degraded conditions (Hynes, 1959; Goodnight, 1973; Milbrink, 1973). Some 337

species of the genus Quistadrilus and IIyodrilus are generally found in areas where the oxygen supply 338

is reduced (Lang, 1984) and where organic enrichment is important, particularly throughout the 339

Laurentian Great Lakes (Brinkhurst & Cook, 1974; Burt et al., 1991). In Port Hope harbour, as in 340

several other harbours in Lake Ontario, Hart et al. (1986) found highest abundances of three species of 341

Oligochaeta Tubificidae in the most contaminated sediments, among which Quistadrilus was the 342

second dominant genus.343

344

Most stations of Lake Saint-François and some stations of Lake Saint-Louis, located in productive 345

waters originating from the Great Lakes, have macroinvertebrate assemblages (Cluster B) similar to 346

these previously observed in Lake Saint-Francois by Pinel-Alloul et al. (1996). Nine indicator genus 347

were characteristics of these habitats, including the Isopoda Caecidotae, the Chironomidae348

Chironomus, Tribelos, and Diaotendipes, the Trichoptera Leptoceridae Triaenodes and the Amphipoda 349

Gammarus. The Chironomid Diaotendipes and the Trichoptera Triaenodes are known to be tolerant to 350

productive environment (Klemm et al., 1990; Johnson et al., 1993). The other indicator taxa such as 351

the Hirudinae, the Hydracarina and the Planarians present important plasticity in their habitat 352

preference (Thorp & Covich, 2001).353

354

Some stations of Lake Saint-Pierre and Lake Saint-Louis, which presented the lowest contamination355

level in sediments, have been grouped together (Cluster C) and were characterized by two indicator 356

taxa: the Nemerta and the Oligochaeta Tubificidae Spirosperma. The freshwater species of Nemerta357

16

are recognized to be patchy and distributed locally in littoral macrophytes (Smith & Pennak, 2001). 358

Nemerteans, with rare exceptions, are carnivorous or scavenging macrophages. Their presence at 359

different stations could simply reflect the presence of preys. On the other hand, the presence of the 360

Oligochaeta Spirosperma in the lowest contaminated environment agrees with some studies which 361

have identified this genus as sensitive to organic pollution and indicator of undisturbed environments362

(Klemm, 1985; Griffiths, 1991; Johnson et al., 1993).363

364

Another group of stations from Lake Saint-Louis and Lake Saint-Pierre (Cluster D) forms a specific 365

assemblage associated to indicator taxa, mainly Chironomidae and Ephemeridae. At the exception of 366

the chironomid Ablabesmyia, all indicator taxa identified for this group are recognized to be 367

representative of oligotrophic medium (low in organic matter) and uncontaminated sites (Klemm et al., 368

1990; Johnson et al., 1993). It is especially the case of the Ephemera Hexagenia. This genus is369

intolerant to organic rich medium, acidic conditions and contaminated sites (Fremling, 1967; Klemm 370

et al., 1990; Reynoldson et al., 2001). The mayflies have been proposed as a good indicator of 371

ecosystem health in many countries (e.g. Fremling, 1970; Landa & Soldan, 1995; Edsall, 2001). The 372

potential of this genus as indicator of good habitat quality is related to its historically abundance in 373

many unpolluted habitats, its disappearance following pollution, and its ability to recover after 374

pollution abatement (Reynoldson et al., 2001). The Ephemera Hexagenia and the three Chironomid375

genus (Axarus, Ablabesmyia and Coelotanypus) found in cluster D were totally absent in all polluted 376

stations of the Montreal harbour. As the Ephemera, the Chironomids have been proposed as indicators 377

of water quality because they may be found in many different physical and chemical conditions in 378

freshwaters (Pinder, 1986). 379

380

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As suggested by Pearson and Rosenberg (1978), our study supports the idea that it may be more useful 381

to use several indicator taxa rather than a unique indicator taxa to characterize macroinvertebrate 382

community variation along pollution or perturbation gradients. One reason is that the presence of a 383

single tolerant species in a site did not signify that this area is polluted or contaminated because many 384

tolerant species can be found in both perturbed and pristine areas.385

386

Influence of sediment contamination and environmental characteristics on macroinvertebrates387

388

When using separately sediment chemical variables and environmental descriptors, we could only 389

explain few of the total variance in macroinvertebrate communities along the studied fluvial section. 390

However for all taxonomic levels (genus vs family) and data (abundance, indicator taxa and 391

presence/absence), environmental descriptors related to water masses, granulometry, DOC and sulphur 392

concentrations in sediments explained higher percentages of macroinvertebrate variation than sediment 393

chemical contamination which had very low influence. Furthermore, the interactions between 394

environmental descriptors and sediment contamination had as much importance as the environmental 395

conditions alone. In many studies, environmental conditions also had a stronger influence on 396

macroinvertebrate communities than sediment contamination (Griffiths, 1991; Clements et al., 1992; 397

Gower et al., 1994). The strong variability in the physical and chemical conditions among water 398

masses flowing in the three fluvial lakes, in the Montreal harbour area, and among stations within each 399

of these four areas, could explain the greatest importance of the environmental variables (water400

masses, depth, sediment grain size, DOC, sulphur, etc.) in structuring the macroinvertebrate 401

communities in the St. Lawrence River. Water masses flowing from the Great Lakes, the Ottawa River 402

and the CUM wastewater are the primary factors explaining the variance in macroinvertebrate 403

abundances at the genus level and the presence/absence of taxa at the genus and family levels. As 404

18

physical and chemical conditions of water masses vary along space and time, macroinvertebrates 405

exposed to changes in these waters must be tolerant to such variations. Pinel-Alloul et al. (2004)406

indicated that environmental stressors also differ along the fluvial section of the St. Lawrence River, 407

depending to inflows of tributaries in the fluvial lakes and the main fluvial channel. Demers and 408

Levasseur (1976) noted strong differences in macroinvertebrate assemblages among 87 stations 409

located in seven sections of the St. Lawrence River (upstream from Lake Saint-François to 410

downstream of Lake Saint-Pierre) in relation to physical and chemical variations in the several water 411

masses differing in their charge in particles, their concentrations of toxic substances in particular and 412

dissolved phases, in trace and major elements and in nutrients (Rondeau et al., 2005). All these factors 413

are known to affect benthic communities (Hellawell, 1986; Burt et al., 1991; Griffiths, 1991).414

415

In RDA ordinations, we found that higher concentrations of Zn, Pb, DOC, and HAP were associated to416

most stations of the Montreal Harbour and stations in Lake Saint-Louis and Lake Saint-Pierre in417

waters originating from the Ottawa River and the CUM wastewater effluent. Many Oligochaeta 418

Tubificidae identified to the family and genus levels were associated with these high levels of 419

contamination. As previously discussed, these groups of organisms are tolerant to high levels of 420

contamination (Hynes, 1959; Goodnight, 1973; Milbrink, 1973). Same taxa were often identified in the 421

RDAs performed using the different taxonomic levels. It is especially the case of the Oligochaeta 422

Tubificidae IIyodrilus, Quistadrilus and Limnodrilus. Many species of these three genus have largely 423

been cited as tolerant organisms to inorganic and organic contaminants (e.g. Klemm, 1985; Burt et al., 424

1991; Adams, 1996; Reynoldson et al., 2001). Since the seventies, the oligochaetes were the group of 425

macroinvertebrates the most often enlisted for biomonitoring and bioassessment of sediment quality in 426

European freshwaters and elsewhere throughout the world (see Brinkhurst & Cook, 1980) for an 427

exhaustive overview) because their development is enhanced in sediments contaminated by organic 428

19

and inorganic pollutants (Lang, 1984; Lafont & Juget, 1985; Verdonschot, 1989). Our study indicated 429

that these three Oligochaeta are also relevant indicator taxa for assessing sediment quality in the St. 430

Lawrence River.431

432

The Porifera Spongillidae Eunapius (POEuna and POSpon) was identified by its presence – absence in 433

the highest concentration of Zn, Pb and DOC occurring in the area of the Montreal harbour. According 434

to Kleem et al. (1990), this genus is strongly tolerant to high concentration of heavy metals. However, 435

the distribution of the Porifera Eunapius was not only restricted to the stations presenting high levels 436

of contaminants. We found this invertebrate in all four studied zones and more specifically in 27 437

stations. Its presence was probably due to its tolerance to a large range of physico-chemical conditions. 438

A recent review on freshwater sponges indicated that sponges can colonize an extremely wide variety 439

of habitats (springs, streams, rapids, estuaries, freshwater and salt lakes, etc.) and are able to tolerate 440

and survive in extreme physico-chemical conditions ranging from permafrost, thermal waters, 441

fluctuating water levels, stagnant to high speed waters, anoxy, oligotrophy to eutrophy, high levels of 442

chemicals, and natural or man-made pollution by hydrocarbons and heavy metals (Manconi & 443

Pronzato, 2008). Some other organisms have also been identified in this zone, such as Platyhelminthes 444

(PLHydr, PLPlag) and Nematods. Kleem et al. (1990) classified these invertebrates as organisms 445

having a wide range of tolerance that are frequently associated with moderate to high levels of organic 446

contamination. In his study carried out in St. Clair River, (Griffiths, 1991) observed the presence of 447

many species of worms and flatworms tolerant to organic and inorganic contamination in the sediment 448

(metals, greases, oil, etc.).449

450

Sometimes associated with percentage of water (humidity) or N/P ratio in the sediment, sulphur was 451

also an important factor explaining variations of macroinvertebrates with all taxonomic levels and data 452

20

used in this study. In our study area sulphur mainly originates from geological source and its gradient 453

corresponding to upstream to downstream gradient with higher concentration observed in the Lake 454

Saint-François. High concentration of sulphur is often associated to low level of oxygen in the 455

sediment. Species more tolerant to hypoxia are also tolerant to sulphide, such as Diptera (Wiederholm, 456

1976; Wiederholm, 1984; Pinder, 1986) and Gastropoda (Goodnight, 1973). In our study, all of these 457

groups of macroinvertebrates have been related to the gradient of sulphur concentrations. Some genus 458

and family of Amphipoda and Isopoda (Caecidotea, Gammarus, Lirceus), Diptera (Chironomus, 459

Dicrotendipes, Tribelos) and Gastropoda (Amnicola, Bithynia, Planorbella and Physella) were 460

identified in stations presenting high concentrations of sulphur. Pinel-Alloul et al. (1996) observed that 461

gastropods can tolerate severe conditions in sediments in Lake Saint-François. They observed an 462

increase in species richness and relative abundance of this group in sediments rich in organic and 463

inorganic pollutants. Some macroinvertebrates may colonize the sides of zones rich in sulphide in such 464

a way to be able to use limited oxygen available and resist toxic effects of hydrogen sulphides. It is 465

probably the case of crustaceans and gastropods in our study, at the opposite of Diptera, these 466

organisms are more motile and can avoid more severe conditions of anoxia and high concentrations of 467

sulphur. Macroinvertebrates may have physiological adaptations to sustain anoxia by producing 468

haemoglobin or ventilating their tubes as for the chironomids (Stief et al., 2005) or by changing their 469

motile behaviour (e.g. movement for gastropods and crustaceans; Salánki et al., 2003). These 470

adaptations could possibly explain why snails were found in areas of low levels of Pb, Zn and HAP 471

contamination.472

473

When using the environmental characteristics only, the N/P ratio was an important variable explaining 474

the variation in macroinvertebrate abundances. This variable was associated with other variables such 475

as NH3, sulphur and depth. The N/P ratio was also identified as primary variable when using both 476

21

explanatory matrices (sediment contamination and environmental characteristics), especially with 477

many stations of Lake Saint-François which presented the highest N/P ratio (5 to 7) because of higher 478

nitrogen concentrations in Lake Saint-François. In this lake, as indicated by vector of environmental 479

descriptors in RDA ordinations, N/P gradient was associated to higher concentrations of TOC and 480

sulphur and a greater proportion of silt in the sediments. Many studies established the correlation 481

between nutrient enrichment of sediment and changes in macroinvertebrate assemblages (Weston, 482

1990; Griffiths, 1991; Gao et al., 2005). The diversity of macroinvertebrates is generally reduced in 483

nutrient-rich stations, reflecting the adverse impacts of nutrient enrichment. Some tolerant organisms 484

thrive in severely organic-rich sediment with high loadings of nutrients and sulphide with low oxygen 485

levels (Milbrink, 1973; Brinkhurst & Cook, 1974; Weston, 1990). In RDA ordinations, the Diptera 486

Chironomidae was closely associated to the N/P ratio. These organisms are extremely tolerant to harsh 487

conditions (Wiederholm, 1976; Pinder, 1986). The chironomids was also associated to high 488

concentrations in THg. This result shows that some taxa of Diptera Chironomidae are well adapted to 489

severe conditions in sediments (e.g. Pinder, 1986; Griffiths, 1991; Stief et al., 2005).490

491

Although THg was retained in all RDA conducted on chemical variables only (Table 3), THg was only492

selected in the RDA performed on abundance at the genus and family levels when using both sediment 493

mixed-contamination and environmental characteristics. The highest concentrations (0.49 to 9.9 494

mg/kg) were mainly observed in the stations located close to the St. Louis River in the south shores of 495

Lake Saint-Louis, and were related to the presence of many industries in this region, and particularly 496

of a former chlore-alkali plant located in the lower reaches of the St. Louis River. It has already been 497

identified as the major source of Hg contamination (Fortin et al., 1994). The area under the influence 498

of the St. Louis River waters is recognized as highly contaminated by mercury in sediments and 499

macroinvertebrates as Gastropods (Désy et al., 2000). Apart the Diptera Chironomidae, other 500

22

macroinvertebrates such as the Gastropoda Amnicola and Gyraulus, the Amphipoda Gammarus, the 501

Trichoptera Nectopsyche and Leptocerus and the Diptera Clinotanypus were associated to stations 502

contaminated in THg. In stations located upstream and downstream of the Saint-Louis River, Willsie 503

& Costan (1996) have observed a greater percentage of Gastropoda, Trichoptera and Amphipoda in the 504

upstream stations where the sediment was the most contaminated in organic and inorganic chemicals. 505

In the St. Marys River, (Griffiths, 1991) found that the Amphipoda Gammarus, and the Gastropoda 506

Amnicola and Gyraulus were associated to stations presenting moderate to severe environmental 507

contamination by THg which concentrations varied between 0.11 to 15.03 mg/kg. Differences among 508

groups of aquatic insects in their sensitivity to heavy metals are well known. Many studies have shown 509

that Trichoptera and some Chironomidae are quite tolerant to high concentrations of heavy metals (e.g. 510

(Warnick & Bell, 1969; Winner et al., 1980; Clements et al., 1988). In agreement with this study, 511

many works carried out in area contaminated by mercury have identified tolerant taxa (e.g. Moore et 512

al., 1979; Suchanek et al., 1995; Willsie & Costan, 1996).513

514

Taxonomic resolution and macroinvertebrate data 515

516

The four different approaches used in this study (genus vs family; abundance vs presence/absence) did 517

not produced the same assemblages of taxa within the four macroinvertebrate groups and did not allow 518

to detect equal and similar indicator taxa within each group. The abundance of taxa at the genus level 519

was found the best approach for detecting more indicator taxa and obtaining better community-520

environment explanatory models. The abundance of taxa at the family level and the presence/absence 521

of taxa at the genus and family levels did not allow identifying indicator taxa in the four associations 522

of stations. In the context of this study, these approaches cannot be used as biological tools to establish 523

relationship between macroinvertebrate assemblages and environmental conditions of sediments and 524

23

waters in the St. Lawrence River. A good biological tool should give a complete scheme of the 525

situation prevailing in all stations and within groups of stations representing the total variation in 526

macroinvertebrate communities. Abundance data at the genus level seems to offer advantage for 527

detecting indicator taxa for the four assemblages of macroinvertebrates along the fluvial section of the 528

St. Lawrence River and gave the more powerful RDA model. In one hand, reducing taxonomic 529

resolution by identifying macroinvertebrates at the family level facilitates sorting, requires a much 530

lower degree of specialisation and lessens time and cost. In the other hand, lack of taxonomic 531

resolution (at the genus level) can decrease sensitivity and reduce the ability to detect more subtle 532

changes (Resh & McElravy, 1984). This is exactly the case of this study when using family level to 533

determine indicator taxa of macroinvertebrate assemblages. Comparing the overall results of the RDA 534

models, we cannot assert that a taxonomic level is better than the other one to establish 535

macroinvertebrate-environment relationships. The percentage of variance in macroinvertebrates 536

explained by chemicals in sediments and environmental characteristics, and their interactions were 537

quite low and comparable among taxonomic levels. Common models also resulted from different data 538

(abundance and presence/absence). Discrepancy exists in the literature about which taxonomic level to 539

use in bioassessment studies. (Reynoldson et al., 2001) found that by increasing the taxonomic level to 540

classify reference sites based on similar macroinvertebrate assemblages (species genus, and family), 541

the family level ranked best, followed by the genus and species levels. Thompson et al. (2003) found 542

that differences between locations were detected when species were aggregated to the family level, but 543

further aggregations at the order and class levels altered the perceived pattern of differences. Resh &544

McElravy (1984) have reviewed 34 papers addressing on the taxonomic considerations, and found that 545

18 studies emphasized the importance of species-level identification while nine studies recommended 546

to use lower resolution at the genus and family levels under appropriate circumstances. According to 547

Resh and McElravy (1984), the importance of identifications level in biomonitoring depends on the548

24

purpose of the study, the level of sensitivity required, the type of analysis being used, and the 549

particular group of organisms of primary interest. The consensus that seems to emerge in the literature 550

is that identification taxa into coarse taxonomic levels is generally quicker, less expensive and needs 551

less taxonomic expertise than identifying to species, thus providing a cost effective method for 552

monitoring responses of macroinvertebrate to environmental changes and contamination. As in our 553

study, many studies have found similar results when using various taxonomic levels (e.g. Olsgard et 554

al., 1998; Urkiaga-Alberdi et al., 1999; Karakassis & Hatziyanni, 2000). Olsgard et al. (1998)555

indicated that patterns of variation among macroinvertebrate community for the various taxonomic 556

levels become more similar with increasing disturbance. As mentioned by Thompson et al. (2003), the 557

cost-efficiency of a benthic monitoring study can be greatly improved if the design of the study 558

optimises the taxonomic resolution necessary to reliably detect an impact. Our study confirms that 559

family level can give comparable information than genus level using presence-absence or abundance560

of macroinvertebrates; However, higher number of indicator taxa were detected at the genus level.561

562

Acknowledgments 563

564

This study is a part of a larger collaborative program funded by the 3rd and 4th phase of the St. 565

Lawrence Action Plan, with the active participation of Environment Canada (Environmental Protection 566

Operations ; Science and Technology Branch), of the Ministère du Développement durable, de 567

l'Environnement et des Parcs du Québec (Centre d’expertise en analyse environnementale du Québec ; 568

Direction des évaluations environnementales ; Direction du suivi de l'état de l'environnement) and 569

Cemagref from Lyon (France). The project was also associated with the sustainable navigation strategy 570

for the St. Lawrence River, which includes aspects such as sustainable dredging management, 571

contaminated site restoration and revision of sediment quality guidelines for contaminated sediment. 572

25

We address special thanks to project steering committee members: C. Bélanger, C. Gagnon, M. 573

Pelletier, and S. Thibodeau from Environment Canada and L. Boudreau, I. Guay, P. Michon and 574

Gaëlle Triffaut-Bouchet from Ministère du Développement durable, de l'Environnement et des Parcs 575

du Québec and Marc Babut from Cemagref. We also want to acknowledge all fieldwork participants, 576

particularly M. Arseneault, G. Brault, A. Lajeunesse, and P. Turcotte who helped over the two 577

sampling years. The identification of the organisms was realized by a private firm (Laboratoires SAB 578

inc.).579

580

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791

792

35

Table 1: Summary of sediment analytical methods for inorganic chemicals, nutrients, organic 793

matter and sediment grain size. 794

Variables Methods and Device Detection limit

Reference

Al As Ca Cd Cr Cu Fe Mn Ni Pb Zn

Argon plasma emission spectrometer after total recoverable extraction (HCL 2.4N/HNO3 8N; 3/1) Optima 3000DV; Perkin ElmerMA, USA

12.0 mg kg-1

0.27 mg kg-1

17.0 mg kg-1

0.22 mg kg-1

3.0 mg kg-1

2.1 mg kg-1

18.0 mg kg-1

1.1 mg kg-1

0.6 mg kg-1

1.2 mg kg-1

2.5 mg kg-1

(CEAEQ, 2007)

THg Thermal decomposition with atomic absorbtionDMA-80; Mileston

0.035 mg kg-1 (CEAEQ, 2007)

Total sulphur infrared detectionLECO SC-444

50 mg kg-1 (CEAEQ, 2006c)

Total Organic Carbon (TOC) Titration 0.05% (CEAEQ, 2006c)

Total Kjeldahl Nitrogen (TKN)

Colorimetric methodTechnicon Model II

100 mg kg-1 (CEAEQ, 2006a)

Total Phosphorus (TP) Colorimetric methodTechnicon Model II

200 mg kg-1 (CEAEQ, 2006a)

Sediment grain size Hydrometric sedimentationHydrometer : type 152H

0.1 % (Pelletier, 2008)

Dissolved Organic Carbon (DOC)*

Infrared detectionShimadzu Model TOC-5000A

0.20 mg L-1 (CEAEQ, 2003e)

*Pore water analysis795

796

797

36

Table 2: Summary of analytical methods for organic chemical in sediment798

Variables Methods and device Detection limit ReferencePCBs Congener method Performed by

Gas Chromatography / Mass Spectrometry Extracted with with acetone/hexane (60:40) and dichloromethanePurification with silica and freshly activated copperGC/MS; Agilent, GC 6890N, MS 5973N

2 - 6 µg kg-1 (CEAEQ, 2003c)

PAHs Performed by Gas Chromatography / Mass Spectrometry Extracted with with acetone/hexane (60:40) and dichloromethanePurification on silicaGC/MS; Agilent, GC 6890N, MS 5973N

0.02 - 0.10 mg kg-1 (CEAEQ, 2003d)

Pesticides organochlorine Performed by Gas Chromatography / Mass Spectrometry Extraction with acetone/hexanePurification on FlorisilGC/MS ; Thermo Quest, GC trace GC et MS trace MS

1-18 µg kg-1 (CEAEQ, 2003a)

Pesticides organophosphate Performed by Gas Chromatography / Mass Spectrometry Extraction acétate d’éthyleGC/MS; Agilent, GC 6890N, MS 5973N

5-260 µg kg-1 (CEAEQ, 2003b)

Pesticides aryloxyacid Performed by Gas Chromatography / Mass Spectrometry Extraction with NaHCO3 and on C-18 columnPurification on silica gelGC/MS; Agilent, GC 6890N, MS 5973N

1-7 µg kg-1 (CEAEQ, 2006b)

37

Variables Methods and device Detection limit ReferencePesticides toxaphene Performed by Gas Chromatography

/ Electron Capture Detector (GC/DCE)GC/ECD ; Hewlett Packard, GC 5890 série II, ECD

3.5 mg kg-1 (CEAEQ, 2003f)

Petroleum Hydrocarbons (C10-C50)

Gas Chromatography Flame Ionization Detector (GC-FID)Extraction hexaneGC/FID; Hewlett Packard, GC 5890 série II, FID

30 mg kg-1 (CEAEQ, 2002)

799800

38

Table 3: Community-chemical models (RDAs) based on macroinvertebrate taxa composition in 801sediments (p<0.05).802

Genus Familyvariable R2 cum Adj R2 cum variable R2 cum Adj R2 cum

AbundanceAll taxa Pb

THgPAHtot

0.080.110.14

0.060.080.09

PbTHg

0.090.13

0.070.09

Indicator taxa ZnTHgPAHtot

0.100.140.17

0.090.110.12

-- -- --

Presence/AbsenceAll taxa Zn

THgPAHtot

0.050.080.10

0.030.050.06

PbAsNiTHg

0.050.090.120.15

0.040.060.070.09

803Table 4: Community-environmental characteristics model (RDAs) based on macroinvertebrate taxa 804composition in sediments (p<0.05).805

Genus Familyvariable R2 cum Adj R2

cumvariable R2 cum Adj R2

cumAbundanceAll taxa Ottawa River

SulphurDOCSandMn

0.070.130.180.210.23

0.050.100.130.150.16

N/PNH3Sulphurdepth

0.100.190.230.25

0.090.160.180.20

Indicator Taxa DOCSulphurSanddepth

0.090.160.200.23

0.070.130.150.17

-- -- --

Presence/AbsenceAll taxa Ottawa River

Great Lakes waterDOCSulphurCUM effluent

0.060.100.130.160.19

0.040.070.090.100.11

Ottawa RiverGreat Lakes waterDOCCUM wastewater

0.060.120.150.18

0.050.080.110.12

Note : CUM : Communauté Urbaine de Montréal806

807

39

Appendice 1 : Macroinvertebrates family and genus used in statistical analysis and their abbreviations 808

show in multivariate analysis809

Phylum Class Family

Abbreviation

family Genus

Abbreviation

genus

ANNELIDA Hirudinae Erpobdellidae HIErpo Mooreobdella HIMoor

Glossophoniidae HIGloss Alboglossiphonia HIAlbo

Batracobdella HIBatr

Glossiphonia HIGlos

Helobdella HIHelo

Oligochaeta Enchytraeidae OLEnch OLEnch

Lumbriculidae OLLum Eclipidrilus OLEcli

Lumbriculus OLlumb

Naididae OLNaid Arcteonais OLArct

Dero OLDero

Nais OLNais

Paranais OLPara

Piguetiella OLPigu

Slavina OLSlav

Specaria OLSpec

Stylaria OLStyl

Unicinais OLUnci

Vejdovskyella OLVejd

Sparganophilidae OLSap Sparganophilus OLSpar

Tubificidae OLTubi Aulodrilus OLAulo

Bothrioneurum OLBoth

Ilyodrilus OLIlyo

Limnodrilus OLLimn

Potamothrix OLPota

Quistadrilus OLQuis

Rhyacodrilus OLRhya

Spirosperma OLSpir

TUBIFICIDEA+soie OLUso

TUBIFICIDEA-soie OLTubi

Polychaeta Sabellidae POSab Manayunkia POMana

ARTHROPODA Arachnida Arrenuridea ARArre Arrenurus ARArre

Hygrobatidae ARHygr Hygrobates ARHygr

Lebertiidae ARLebe Lebertia ARLebe

Limnesiidae ARLimn Limnesia ARLimn

Oxidae AROx Oxus AROxus

Unionicolidae ARUnio Unionicola ARUnio

Malacostraca Gammaridae MAGamm Gammarus MAGamm

Asellidae MAAse Caecidotea MACaec

Lirceus MALirc

Ostracoda Candoniidae OSCand Candona OSCand

Cyprididae OSCyp Herpetocypris OSHerp

40

Isocypris OSIsoc

Insecta Elmidae INElm Dubiraphia INDubi

Ceratopogonidae INCera Probezzia INProb

Chironomidae INChir Axarus INAxar

Chironomus INChir

Cryptochironomus INCryp

Demicryptochironomus INDemi

Dicrotendipes INDicr

Harnischia INHarn

Microtendipes INMicr

Pagastiella INPaga

Parachironomus INParc

Paralauterborniella INParl

Paratendipes INPart

Phaenopsectra INPhae

Polypedilum INPope

Tribelos INTrib

Xenochironomus INXeno

Pseudochironomus INPseu

Cladotanytarsus INClad

Paratanytarsus INPrat

Rheotanytarsus INRheo

Tanytarsus INTany

Cricotopus INCric

Epoicocladius INEpoi

Thienemanniella INThie

Ablabesmyia INAbla

Clinotanypus INClin

Coelotanypus INCoel

Procladius INProc

Thienemannimyia INThiy

Potthastia INPott

Caenidae INCea Caenis INCaen

Ephemeridae INEph Hexagenia INHexa

Pyralidae INPyr Acentria INAcen

Sialidae INSia Sialis INSial

Gomphidae ONGom Stylurus INStyl

Coenagrionidae INCoen Coenagrion INCoen

Dipseudopsidae INDips Phylocentropus INPhyl

Hydroptilidae INHydr Agraylae INAgra

Hydroptila INHydr

Leptoceridae INLept Ceraclea INCera

Leptocerus INLept

Mystacides INMyst

Nectopsyche INNect

Oecetis INOece

Triaenodes INTria

41

Polycentropodidae INPoly Polycentropus INPoly

CNIDARIA Hydrozoa Hydridae HYHydr Hydra HYHydr

MOLLUSCA Bivalva Dreissenidae BIDrei Dreissena BIDrei

Sphaeriidae BISpha Pisidium BIPisi

Sphaerium BISpha

Unionidae BIUni Elliptio BIElli

Lampsilis BILamp

Gastropoda Bithyniidae GABith Bithynia GABith

Hydrobiidae GAHydr Amnicola GAAmni

Birgella GABirg

Probythinella GAProb

Valvatidae GAValv Valvata GAValv

Viviparidae GAViv Cipangopauludina GACipa

Ancylidae GAAnc Ferrissia GAFerr

Lymnaeidae GALym Stagnicola GAStag

Physidae GAPhys Physella GAPhys

Planorbidae GAPlan Armiger GAAmi

Gyraulus GAGyra

Helisoma GAHeli

Planorbella GAPlan

Promenetus GAProm

NEMATODA Nemato

NEMERTA Enopla Tetrastemmatidae NETetr Prostoma NEPros

PLATYHELMINTHES Plagiostomidae PLPlag Hydrolimax PLHydr

Planariidae PLPlan Dugesia PLDuge

PORIFERA Demospongiae Spongillidae POSpon Eunapius POEuna

810

811

42

Figure captions812

Figure 1: Study area and location of the 59 stations in the three fluvial lakes (Saint-François, Saint-813

Louis and Saint-Pierre) and the Montreal harbour area in the St. Lawrence River (Canada).814

Figure 2: Biplots of the first two axes of the PCoA ordination of sites explained by macroinvertebrate815

assemblages based on A) genus and B) family abundances.816

Figure 3: Biplots of the first two axes of the PCoA ordinations of sites explained by macroinvertebrate 817

assemblages based on A) genus and B) family presences/absences.818

819

Figure 4: Biplots of the first two axes of the RDA ordination of the macroinvertebrate taxa 820

composition explained by chemical concentrations in sediments and environmental characteristics 821

based on A) genus and B) family abundances (for legend see Appendice 1).822

823

Figure 5: Biplots of the first two axes of the RDA ordination of the macroinvertebrate taxa 824

composition explained by chemical concentrations in sediments and environmental characteristics 825

based on A) genus and B) family presences/absences (for legend see Appendice 1).826

827

Figure 6: Biplots of the first two axes of the RDA ordination of the macroinvertebrate taxa 828

composition explained by chemical concentrations in sediments and environmental characteristics for 829

significant indicator genus (for legend see Appendice 1)830

831

Figure 7: Proportion of variance in macroinvertebrate communities explained by chemical 832concentrations in sediments, environmental characteristics and their interactions for A) genus 833abundances, B) significant indicator genus abundances, C) family abundances, D) genus 834presences/absences data and E) family presences/absences data.835

836

43

Masson et al ; Figure 1837

838

839

840

841

44

Masson et al ; Figure 2842

843

45

Masson et al ; Figure 3844

845

46

Masson et al; Figure 4846

847

848

849

850

47

Masson et al ; Figure 5851

852

853

48

Masson et al ; Figure 6854

855

856

49

Masson et al ; Figure 7857

858

859

860

861