Impact of Dredged-material Disposal on Soft-bottom Communities in a Recurrent Marine Dumping Area near to Guadalquivir Estuary, Spain

Depósito de investigación de la Universidad de Sevilla https://idus.us.es/ “This is an Accepted Manuscript of an article published by Elsevier in: MARINE ENVIRONMENTAL RESEARCH on 2018, available at: https://doi.org/10.1016/j.marenvres.2018.05.010” Manuscript Details Manuscript number MERE_2018_93_R1 Title Impact of dredged-material disposal on soft-bottom communities in a recurrent marine dumping area near to Guadalquivir estuary, Spain. Short title Impact of dredged-material disposal in a recurrent marine dumping area. Article type Full Length Article Abstract This study assesses the effects of dredged material disposal in a recurrent marine dump near the Guadalquivir Estuary (south-western Spain). We compared the changes observed with two reference areas combining a classical ecological approach with new stable isotope techniques to analyse trophic structure. We detected permanent changes in the macrofaunal community structure as well as in the diversity and biotic indices applied, which showed higher values in the disposal area. The community in the marine dump had lost the natural temporal variations observed in the reference areas. These effects could be due to the last disposal event carried out in the summer of 2015 or to the recurrent disposals since 2010. Despite the structural changes shown by the benthic community, these impacts were not reflected in the food web structure of the marine dump. Our results confirm the high variability of disposal disturbances. Hence, we recommend performing studies in every disposal event, merging different functional and structural approaches. Keywords disposal; macrobenthic community; stable isotopes; food web; Gulf of Cadiz Taxonomy Invertebrates, Environmental Pollution, Biological Sciences Corresponding Author Inigo Donázar-Aramendía Corresponding Author's Institution LBM Seville University Order of Authors Inigo Donázar-Aramendía, J. Emilio Sánchez-Moyano, Isabel García-Asencio, Juan-Miguel Miro, Cesar Megina, José Carlos García-Gómez HIGHLIGHTS • Impacts of dredge material disposal in a recurrent marine dump were compared with two control areas. • Macrofaunal community of the disposal area showed higher values in diversity and richness over the sampling periods. • Control areas showed temporal differences while the disposal area remained stable. • The recurrent disposals did not seem to affect the food web structure. 1 Impact of dredged-material disposal on soft-bottom communities in a recurrent 2 marine dumping area near to Guadalquivir estuary, Spain. 3 Donázar-Aramendía, I.; Sánchez-Moyano, J.E.; García-Asencio, I.; Miró, J.M.; Megina, 4 C.; García-Gómez, J.C. 5 Laboratorio Biología Marina, Seville Aquarium R+D+I Biological Research Area., Dpto. 6 Zoología, Facultad de Biología, Universidad de Sevilla, Avd. Reina Mercedes 6, 41012 7 Sevilla, Spain 8 Corresponding author: I. Donázar-Aramendía. email: [email protected] 9 ABSTRACT 10 This study assesses the effects of dredged material disposal in a recurrent 11 marine dump near the Guadalquivir Estuary (south-western Spain). We compared the 12 changes observed with two reference areas combining a classical ecological approach 13 with new stable isotope techniques to analyse trophic structure. We detected 14 permanent changes in the macrofaunal community structure as well as in the diversity 15 and biotic indices applied, which showed higher values in the disposal area. The 16 community in the marine dump had lost the natural temporal variations observed in the 17 reference areas. These effects could be due to the last disposal event carried out in the 18 summer of 2015 or to the recurrent disposals since 2010. Despite the structural 19 changes shown by the benthic community, these impacts were not reflected in the food 20 web structure of the marine dump. Our results confirm the high variability of disposal 21 disturbances. Hence, we recommend performing studies in every disposal event, 22 merging different functional and structural approaches. 23 KEYWORDS: disposal, macrobenthic community, stable isotopes, food web, Gulf of 24 Cadiz 25 1. INTRODUCTION 26 Both dredging and the dumping of dredged material are common practices 27 around the world and are one of the most serious environmental concerns for coastal 28 management (Marmin et al., 2016; Moog et al., 2015; Van Dolah et al., 1984). These 29 practices are particularly developed in estuaries where sedimentation patterns are high 30 and may be accelerated by human activities (Cesar et al., 2014). However, dredging is 31 essential to maintain security in navigation and to support trade and economic 32 sustainability (OSPAR, 2008; Bates et al., 2015). Although relocation of dredged 33 material is one of the most important concerns in those activities, much of the material 34 dredged is still disposed at sea for economic reasons (Harvey et al., 1998; Katsiaras et 35 al., 2015; Tornero and Hanke, 2016). Dredging and disposal of dredge material may 36 cause environmental problems in coastal and marine areas, both physically and 37 through contaminants (e.g. Bolam et al., 2006; Bolam and Rees, 2003; Cesar et al., 38 2014; Fredette and French, 2004; Guerra et al., 2009, 2007; OSPAR, 2008). Within the 39 implementation of the European Water Framework Directive, the improvement of our 40 knowledge of human impacts is critical for marine management and conservation 41 (Marmin et al., 2016). 42 Effects of dumping on coastal ecosystems depend on several factors, such as 43 the disposal method, the amount of sediment disposed, the physical and chemical 44 characteristics of the dredged and receiving sediment, depth, the oceanographic and 45 sedimentary conditions of the receiving habitat, season and the adaptations and 46 composition of the inhabitant community (Katsiaras et al., 2015; Simonini et al., 2005b, 47 and references therein). Dredged material disposal may affect marine organisms 48 through physical alterations such as the smothering of the sea bottom, in addition to 49 increased turbidity and enrichment of pollutant, organic matter and nutrient 50 concentrations in the sediment, among other impacts (Cesar et al., 2014, and 51 references therein). Furthermore, these impacts may lead to important habitat changes 52 through long term effects (Powilleit et al., 2009). Benthic macrofauna are the organisms 53 that are most sensitive to these impacts because of their relative immobility (Simonini 54 et al., 2005b; Taupp and Wetzel, 2013). However, effects on primary production and 55 changes in species composition can have an impact on the whole food web structure 56 (Pezy et al., 2017). Nutrient inputs often affect the basal resources, sometimes 57 converting a complex food web to a more homogeneous system (Rooney et al., 2008). 58 Analysing community trophic structure is one way to assess the nature and magnitude 59 of human impacts (Hussey et al., 2014). 60 When a potential anthropogenic disturbance is repeated over time, the 61 recurrence of this event is also an important factor too (Glasby and Underwood, 1996; 62 Villnäs et al., 2013). On the first hand, sediment disposal after dredging operations can 63 be consider a short-term or “pulse” disturbance, in the sense outlined by Glasby and 64 Underwood (1996). On the other hand, the sediment disposed, if it differs from the 65 native sediment, may constitute permanent or a long-term change in the affected 66 habitat. Recurrent sediment disposal operations and the accumulation of dredged 67 material could generate a series of short-term responses in the biological community, 68 followed by a recovery (to some extent) and convergence to a previous state, a 69 permanent change or a combination of these two processes (Underwood, 1994). 70 There are several studies addressing the effects of disposal in offshore 71 environments (e.g. Smith and Rule, 2001; Stronkhorst et al., 2003; Zimmerman et al., 72 2003; Simonini et al., 2005b; Ware et al., 2010; Bolam et al., 2011; Bolam, 2012; 73 Taupp and Wetzel, 2013; Cesar et al., 2014; Katsiaras et al., 2015; Marmin et al., 74 2016). However, several authors have highlighted the divergent results obtained in 75 disposal impact studies and concluded that the potential environmental effects must be 76 evaluated case by case (Bolam et al., 2006; Bolam and Rees, 2003; Harvey et al., 77 1998; Katsiaras et al., 2015; OSPAR, 2008; Simonini et al., 2005b). Furthermore, to 78 our knowledge, the effects of disposal of a recurrent and active marine dump on the 79 benthic community have not been widely studied (Bolam et al., 2011). In addition, the 80 impact of sediment disposal on the food web has been studied even less (e.g. Pezy et 81 al., 2017). 82 In this study we evaluated the impact of dredge sediment deposition on a 83 recurrent marine disposal area in south-western Spain. The Guadalquivir estuary 84 provides access to Seville harbour, the only inland harbour in the Iberian Peninsula, 85 through a 90-km long navigation channel. The strongly modified course and 86 sedimentary dynamics made some dredging work necessary every few years to 87 maintain navigability (Díez-Minguito, 2012). Part of the sediment dredged along the 88 channel is brought ashore for storage, while the other part goes to beach nourishment 89 and some is disposed in an authorised marine area established in 2010. We compared 90 the changes observed in the disposal area with two nearby control areas. Specifically, 91 this study is focused on the following objectives: (i) to assess the response of the 92 benthic community to recurrent sediment discharges (ii) to evaluate the effect of the 93 most recent disposal event (iii) to determinate the effects on the food web structure and 94 (iv) to describe the temporal variation of a biological community in a recurrently 95 stressed area. 96 2. MATERIAL AND METHODS 97 2.1 Study area 98 The marine disposal area is situated five miles offshore in an open water area in 99 front of the river mouth of the Guadalquivir estuary, south-western Spain (Fig. 1). The 100 bottom is 20 metres in depth. Sediments are mainly composed of fine sand and mud 101 and are affected by terrigenous inputs of the Guadalquivir River and the hydrodynamic 102 conditions of the Gulf of Cádiz, with predominant east-ward currents (Sainz and Ruiz, 103 2006). These currents are derived from the North Atlantic surface waters and have the 104 greatest effect on the sediment distribution (Sainz and Ruiz, 2006). The marine dump 105 has a rectangular shape with a surface of 66.26 ha (Fig. 1). The sea bottom near this 106 area has similar sedimentary characteristics (Gonzalez and Dias, 2004) and biological 107 communities (Fa et al., 2003). This dump has been receiving dredge material from 108 harbours and the Guadalquivir estuary in four events since 2010 (2010: 338.652 m3, 109 2011: 353.488 m3, 2013: 354.795 m3 and 2015: present study), (data from Autoridad 110 Portuaria de Sevilla (APS)). 111 From mid-august to the first week of September 2015, dredging operations for 112 maintenance of the navigation channel of the Guadalquivir estuary and Bonanza port 113 were performed and 314.275 m3 of the extracted sediment was discharged in the 114 disposal area. 115 Figure 1. Location of the disposal and control areas. 116 2.2 Sampling Design 117 Three sampling areas were established in the same environment: one within the 118 marine disposal area (DA) and two controls located approximately three miles from the 119 affected area (C1 and C2) (Fig 1). Controls were located at the same depth in a very 120 similar area with equal hydrological and geomorphic characteristics (Sainz and Ruiz, 121 2006). Distances between controls and the disposal area were enough to avoid any 122 possible impacts. In total, five sampling surveys were carried out: twice before the last 123 dumping event (to test the previous affections of the recurrent disposals) and three 124 times after the last disposal event of summer 2015 (to analyse both effects of this last 125 perturbation and the temporal variation of the system). Before: June and July 2015. 126 After: October 2015 (one month after the last disposal event), March and August 2016, 127 (6 and 12 months after the event, respectively). 128 At each control and disposal area, three stations were randomly placed. In each 129 station, three samples were taken for macrofaunal analysis with a van Veen grab (0.15 130 m2 total sampling area per station and date). For posterior analysis, all stations were 131 considered replicates of each area. Macrofaunal samples were sieved through a 0.5 132 mm size mesh. Infauna was preserved in ethanol (70%), and stained with Rose Bengal 133 for subsequent identification and quantification to species level where possible. A 134 sediment sample was taken for granulometric analysis. Grain size distribution was 135 measured as percentages of 100 gr of dry sediment sieved through a sieve net (5 mm, 136 2 mm, 1 mm, 0.5mm, 0.250 mm, 0.125 mm, 0.063 mm). 137 For the isotope analysis of carbon and nitrogen, fauna were collected in three of 138 the five surveys (June 2015, October 2015 and August 2016) with a van Veen grab 139 (0.05 m2) and an epibenthic sledge (46 x 25 cm, 2.5 mm net mesh size). The number 140 of samples was sufficient to obtain a representative number of species of the benthic 141 community. All samples were sieved by 0.5 mm mesh sieve and organisms were 142 sorted by species, transferred to the laboratory in refrigerated containers and kept alive 143 for 24 h to evacuate their gut content. In order to determine the isotopic composition of 144 sediment organic matter (SOM), sediment was taken from the upper 2 cm of a van 145 Veen grab sample. In the lab, species identification was confirmed and fauna were 146 rinsed in distilled water. Muscle tissue samples of fish and molluscs were dissected. A 147 pool of several organisms was used when the individuals had low biomass values (< 148 0.3 mg dry weight). Organisms were dried at 60 °C for at least 48h and ground to a 149 powder. Sediment samples were acidified with 0.1 M HCl to remove carbonates, and 150 were then oven dried at 60 °C. Subsamples of powdered materials were weighed to the 151 nearest 0.3 mg and placed into tin capsules for δ 13C and δ 15N determinations. All 152 samples were combusted at 1020 °C using a continuous-flow isotope-ratio mass 153 spectrometry system by means of Flash HT Plus elemental analyser coupled to a 154 Delta-V Advantage isotope ratio mass spectrometer via a CONFLO IV interface 262 significance over and above the potential variability in the effect among sampling dates; 263 it is interpretable as significant even if the interaction between factors “Dates” and 264 “Impact vs Control” were also significant (p = 0.0024). Instead, the results did not show 265 a significant interaction between “Time” and “Impact vs Control” (p = 0.4388). These 266 results indicate a different pattern of change in the control and the disposal area across 267 the sampling dates, but not globally before and after the sediment disposal on October 268 2015. PERMANOVA results of the separated analysis of the disposal area showed no 269 significant differences (p = 0.1027) across the sampling dates. Conversely, there were 270 different significant community structures in the controls across the sampling dates (p < 271 0.0001). 272 Table 3. PERMANOVA results of the Bray-Curtis similarity matrix based of the square 273 root transformed data. *p estimation obtained by Monte Carlo sampling. df MS Pseudo-F p Unique perms Impact vs Control 1 5,635 6.3079 0.0205 9626 Time 1 2,113 1.0245 0.4368* 10 Dates(Time) 3 2,062 4.4828 0.0001 9881 Impact vs ControlxTime 1 949.63 1.063 0.4388 9648 Impact vs ControlxDates(Time) 3 893.37 1.9422 0.0024 9873 Res 35 459.99 Total 44 274 SIMPER analysis (Table S1) showed dissimilarities between controls and the 275 disposal area for each sampling date. Before the last dumping event, differences were 276 mostly due to the higher abundance of the tanaid Apseudopsis latreillii and the 277 polychaete Sternaspis scutata in the controls, and the polychaetes Magelona 278 papillicornis, Spiophanes kroyeri, Nepthys hombergii, Sigambra parva, two species of 279 the genus Mediocorophium and the cumacean Eudorella truncatula in the disposal 280 area. 281 SIMPER analysis comparing dates within controls (Table S2) showed that 282 differences between June and July 2015 were, firstly, due to several species, such as 283 A. latreillii and the mollusc Hyala vitrea, which began to increase their abundance in 284 July 2015. Secondly, new species such as U. tipica and the bivalve Hemilepton nitidum 285 occurred in this last month. In October, the abundance of several species experienced 286 a high increase (A. latreillii, Aonides oxycephala, Capitella capitata, U. tipica, H. 287 nitidum, H. vitrea). In March 2016 the abundances of these species and others 288 decreased to June 2015 levels. The polychaete Terebellides stroemi occurred in this 289 month. In August 2016, abundances of some species increased while others 290 decreased: e.g. H. vitrea and C. gibba began to increase while others, such as A. 291 latreillii, E. truncatula and T. stroemi decreased. 292 On the other hand, in the disposal area (Table S3), SIMPER results showed 293 that the most abundant species such as A. latreillii and U. tipica followed the same 294 patterns as in the controls areas, but with a lower abundance increase. On the 295 contrary, as with control areas, in October 2015, several species, such as 296 Mediocorophium sp., Spiophanes kroyerii and Lumbrineris latreillei, suffered a 297 decrease in their abundance. In March 2016 A. latreilii decreased while U. tipica 298 remained at the same value until August 2016, where it practically disappeared from 299 this area in addition to H. nitidum. A general increase in the abundance of other 300 species was observed. 301 Isotope graphs showed practically no differences in food webs between the 302 three areas (Fig. 5). The carbon isotope signal of SOM in the disposal area showed 303 different signals over time, whilst these signals were similar over time in the control 304 areas. The disposal area showed a more enriched carbon value in June 2015, which 305 became depleted over time. Graphs also suggest that trophic interactions were similar 306 in the three areas (Fig. 5). However, the species Apseudopsis latreillii presented a 307 clear difference in the disposal area; the nitrogen signal experienced an increase in the 308 most recent survey, while it remained at the same levels in the control areas. Disposal Area C1 C2 δ15N Glycera tesselata Nephtys hombergii Sternaspis scutata Apseudopsis latreillii Nucula hanleyi Sediment Turritella turbona 309 Figure 5. δ13C (x-axis) and δ15N (y-axis) means of the organisms collected in the 310 Disposal area (upper), C1 (middle) and C2 (bottom). Arrows represents isotopic 311 variation over the three sampling dates. Polychaetes have been separated for better 312 visualisation (left column). The x-axis is not always on the same scale. 313 314 4. DISCUSSION 315 The community structure in the disposal area displayed marked differences in 316 relation to the nearby environment. Shannon’s diversity, richness and the biotic indices 317 showed that the disposal area had developed a more diverse and rich community with 318 higher EQS values than control areas established a few kilometres away. On the other 319 hand, the most recent disposal event, carried out in the summer of 2015, seemed not δ13C δ13C 320 to permanently affect to any of the indices measured, nor the community structure. 321 Furthermore, other findings in this disposal area include the fact that the natural shifts 322 in abundance and the community structure of the control areas were absent in the 323 disposal area. However, it is difficult to establish whether these effects could be due to 324 the most recent disposal event, or to the recurrent disposals since 2010. On the other 325 hand, these effects on the community have not been reflected clearly in the trophic 326 food web. Although isotopic sediment signals in the disposal area could be influenced 327 by the historical disposals, the isospace occupied by all the organisms was similar in 328 the three areas. This suggests the same use of basal resources, as well as the same 329 trophic interactions over time. Only a tanaid species showed an important increase in 330 their nitrogen value a year after the disposal. 331 Our results showed that univariate indices such as diversity and richness 332 reflected the changes driven by the historical disposal operations over time better than 333 the biotic indices AMBI and BENFES. Only, BENTIX was able to differentiate the EQS 334 of the disposal area from the controls, however, it did not show any pattern across the 335 sampling dates. This agrees with Simboura et al. (2007), who found that BENTIX was 336 useful for assessing the long term trends of community health in a metalliferous waste 337 dumping. Total abundance and the Shannon’s diversity indices also assessed the 338 temporal changes over the sampling dates more effectively. This agrees with Katsiaras 339 et al. (2015) and Ware et al. (2009), who pointed out that most sensitive ecological 340 indicators of dumping effects were richness and abundance rather than AMBI or 341 BENTIX. On the other hand, Taupp and Wetzel (2013) found that species richness, 342 Shannon’s diversity and AMBI among others were able to reflect the effects of dumping 343 in estuaries. 344 Most of the species found in the control areas are characteristic of muddy 345 bottoms, while a mixture of species characterised by both sandy and muddy bottoms 346 were observed in the disposal area. The latter could be explained by the translocation 347 of species from the original dredged material and by the immigration of species from 348 the surrounding muddy community. In a soft bottom, habitat variability and structure are 349 considered as key factors in biodiversity patterns (Hewitt et al., 2008; Reise, 2002; 350 Zajac, 2008), and, generally, it is widely accepted that environments that show a great 351 range of structural components can support a larger number of species and greater 352 abundance (Carvalho et al., 2017). The sea bottom in the control areas was 353 characterised by a very stable sedimentary and hydrological environment, typical of 354 areas close to the mouth of great rivers, and host a biocoenosis typical of coastal 355 terrigenous muds (Bellan-Santini et al., 1994) or Amphiura assemblages according to 356 other authors, such as Thorson (1957). Consequently, these areas show a well-defined 357 animal assemblage, so that the higher diversity and species richness in the disposal 358 area could be due to the increase in structural complexity by the regular addition of 359 more complex sediments characterised by lower % of fines. Johnson and Frid (1995), 360 found similar results and suggested that it appears to be consistent with predictions of 361 the Intermediate Disturbance Hypothesis (IDH) proposed by Connell (1978). 362 Differences in the temporal variation of the abundance in the disposal area 363 compared to the controls could be explained by two factors: (1) Changes suffered by 364 this area over the years has modified the natural seasonality of the species or (2) The 365 most recent disposal event could lead to physical and chemical disturbances, which 366 affect the macrofaunal community. Disposal could affect seasonal recruitment, 367 affecting the species abundance (Manning et al., 2014). In fact, SIMPER analysis 368 showed a decrease in the abundance of some species in the disposal area after the 369 disposal of 2015. Furthermore, significant interaction between “Impact vs Control” and 370 “Dates” in the abundance analysis, as well as the community structure, indicated a 371 possible effect on the impacted area. Analyses revealed no changes in the disposal 372 area over the dates, while control areas showed natural differences. 373 According to a Before After Control Impact (Underwood, 1991), if the putatively 374 impacted area had changed over time from before to after the most recent disposal 375 event, with a different pattern when compared to the controls, it would mean a 376 permanent impact from the most recent disposal event. However, the absence of any 377 interaction between the factors “Impact vs Control” and “Time” indicated that there was 378 not a permanent effect from the most recent disposal. The relatively high diversity, 379 richness and abundance found after the disposal could be attributed to a gradual and 380 homogenous deposition of dredge sediment over a relatively large area. The thin layer 381 created would permit the survival of a high proportion of different species, as in the 382 study carried out by Simonini et al. (2005b). Organisms have the capacity to burrow 383 into the sediment in order to avoid burial, making them capable of tolerating these 384 perturbations (Powilleit et al., 2009). This would be in accordance with Marmin et al. 385 (2016), who proposed that more dispersive disposals over a wider area were 386 recommended, rather than depositions at a single point. Furthermore, organisms 387 situated in a perturbed zone present more resilience to perturbations (Bolam and Rees, 388 2003). Furthermore, a rapid recovery after a disposal has been attributed to the great 389 potential of juvenile settlement and adult colonisation from the edges (Bolam and Rees, 390 2003; Fredette and French, 2004; Munari and Mistri, 2014). 391 Several studies have found recovery in disposal areas in terms of abundance, 392 richness and diversity, but not in terms of the community structure (OSPAR, 2008). 393 Changes in macrofaunal community structure have been reported in many disposal 394 effect studies: (e.g. Harvey et al., 1998; Zimmerman et al., 2003; Witt et al., 2004; 395 Bolam et al., 2006; Powilleit et al., 2006; Ware et al., 2010; Taupp and Wetzel, 2013; 396 Munari and Mistri, 2014; Katsiaras et al., 2015). However, other studies, such as 397 Roberts and Forrest (1999), Smith and Rule (2001), Stronkhorst et al. (2003), Simonini 398 et al. (2005b) and Bolam et al. (2011), found scarce indication of impact in their 399 respective disposal areas. Our results pointed to an influence of the dredge material 400 disposal in terms of community structure and a lack of temporal variation in the 401 disposal area. Conversely, the control areas showed a very similar community trend 402 with significant temporal variations. This could again be related to the changes 403 established by the periodic sediment input from maintenance dredging for channel 404 navigation in the Guadalquivir River, or at least to the most recent disposal event in the 405 summer of 2015. 406 Recovery patterns after a disturbance, such as dredging and disposal 407 operations, seem to take different pathways in every study, and depend on several 408 factors (Newell et al., 1998). Bolam & Rees (2003) pointed out that communities of 409 naturally stressed environments could recover better than more stable zones. 410 Shallower zones with physical disturbances tend to take less than one year to recover 411 in many cases, while deeper, more stable zones take more time to converge with the 412 initial community structure. Despite the fact that an assessment of recovery in an on- 413 going disposal area is difficult, our results are consistent with OSPAR (2008), where it 414 was pointed out that community structure often fails to converge with natural reference 415 areas. SIMPER analysis showed that one month after the last disposal event was the 416 date with the highest similarity between the control and the disposal area. This could 417 be explained by the decrease of some species in the disposal area that were 418 contributing to these differences before. In this month, the abundance of some 419 abundant species also increased in both control and disposal areas. Six months and a 420 year after the summer 2015 disposal, the community structure of the disposal area 421 showed more dissimilarity with the control areas. This was due to the different patterns 422 of change in terms of species common to both the controls areas and the disposal 423 area, and the appearance of species in the disposal area that were not present in the 424 control areas. 425 The tanaid Apseudopsis latreillii was the main species contributing to the 426 dissimilarity found between the disposal area and the control areas after the disposal of 427 2015. This organism did not experience such a pronounced increase in its abundance 428 in the disposal area as it did in the two control areas. This species usually spawns 429 during late summer and early autumn, reaching high densities in the soft bottoms of 430 this geographical area (Sánchez-Moyano et al., 2007). de-la-Ossa-Carretero et al. 431 (2010) indicated that A. latreillii responds to sewage disposal with a decrease in 432 population density and, furthermore, smaller juvenile individuals appear to be 433 particularly sensitive, since these individuals normally live near the surface and are 434 more exposed to disturbance. Consequently, the coincidence of dumping with the 435 reproductive peak may have adversely affected the populations of this species. 436 However, another species that was very abundant among all studied areas was the 437 decapod Upogebia tipica (and also, in smaller numbers, U. deltaura), which was not 438 affected by the dumping. Upogebiidae usually need sandy and muddy substrates to 439 construct long burrows (deeper than 20–30 cm) where they obtain shelter, protection 440 from predators and appropriate conditions for feeding and reproduction (Coelho et al., 441 2000). Upogebia spp. occur in the coast of the Gulf of Cádiz between depths of 20 and 442 40 m and generally show a reproductive event during the spring-summer period with a 443 planktonic larval phase of around three weeks (Pires et al., 2013). Their reproductive 444 cycle prior to sediment disposal, and their deep burrows, could be the reasons why 445 there were no differences between the control and the disposal areas. Similar results 446 have been obtained with other abundant burrowing species, such as the polychaetes 447 Lumbrineris latreilli, Nephthys hombergii and Sternaspis scutata. 448 Carbon isotopic signals of sediment in the disposal area could suggest a 449 perturbation on the impacted area before the disposal of summer 2015 due to the 450 periodical inputs of more carbon-enriched sediments from the estuary. However, this 451 point was not reflected in the trophic food web, since analysed species showed similar 452 carbon signal in the disposal area and in the two control areas. Since all species 453 showed similar isotope signals over time, it suggests that the origin of organic matter 454 was similar in the three areas. Furthermore, after the disposal in the summer of 2015, 455 the isotopic signal of the sediment in the disposal area was similar to the control areas. 456 Nitrogen isotopic values also suggest similar trophic niches for most organisms in the 457 three areas across all sampling dates. However, Apseudopsis latreillii showed an 458 important increase in their nitrogen values in the marine dump with respect to the 459 control areas in the August 2016 survey. Variation in the tanaid isotopic signal could be 460 attributed to the most recent disposal event, although more specific studies would be 461 necessary to demonstrate this question. Change in diet composition is not immediately 462 reflected by tissue isotopic values, which integrate trophic information over a certain 463 period of time (Sampaio et al., 2010; Sweeting et al., 2005). This could explain the lack 464 of differences in the October 2015 survey. Since there were no changes in nitrogen 465 signal of the basal resources, increase in the nitrogen signal of that species could be 466 explained by a change in the degree of trophic omnivory (Post and Takimoto, 2007). 467 These results contrast with other studies where changes in the trophic structure of 468 disposal impacted areas have been found (Bolam, 2012; Munari and Mistri, 2014; Pezy 469 et al., 2017; Simonini et al., 2005a). However, these studies were focused on functional 470 traits and secondary production rather than a stable isotopic approach. 471 5. CONCLUSION 472 The recurrent disposals constitute pulse disturbances, but repeated periodically, 473 which could produce: (1) recurrent pulse or short-term responses in the biological 474 community followed by a convergence towards the reference communities, (2) a 475 permanent change or (3) a combination of these two effects (Underwood, 1994). The 476 results of this study suggest that a permanent change exists. However, we cannot 477 discard some short-term effects of most recent disposal event such as the affection of 478 the recruitment of some species. 479 The impact of depositing dredge material in marine environments depends on 480 various factors, such as the amount of sediment, dumping season, water depth, 481 currents and similarity of dredge material and the native sediment (Powilleit et al., 482 2006; Marmin et al., 2014). For this reason, the impacts of dredge-material disposal are 483 mostly site-specific (OSPAR, 2008). There are few studies assessing the effects of 484 dumping in a historic marine dump with well-established macrofaunal communities 485 such as Ware et al. (2009, 2010) for example. Our data suggest that in the disposal 486 area, where a disposal operation occurs periodically, there have been changes that 487 have affected biological characteristics permanently. Contrary to other studies, the 488 continuous disposal of dredge material from the Guadalquivir estuary has increased 489 richness and diversity indices, although these historical impacts, as well as the most 490 recent disposal event, could have led to the natural loss of seasonality in the marine 491 dump. Conversely, the food web has not been affected. Furthermore, disposal timing is 492 an important factor to consider. To minimise the impact on soft-bottom communities, 493 dredging and disposal operations should avoid the main reproduction and recruitment 494 periods and be developed, where technical aspects make it possible, in winter months 495 (Sánchez-Moyano et al., 2004; Ceia et al., 2013). Our results confirm the high 496 variability of impacts due to disposal operations and confirm again the ‘site-specific’ 497 character of these perturbations. We suggest that impact studies are needed in every 498 disposal operation work across temporal and spatial scales. Classic approaches and 499 new techniques are also required to assess the effects of these anthropogenic impacts 500 at different levels in macrofaunal soft-bottom communities such as functional and 501 trophic traits. Using stable isotope techniques to assess effects of these perturbations 502 appears to be an interesting tool that has never been used in dredging and dumping 503 studies. 504 6. ACKNOWLEDGMENTS 505 We thank Autoridad Portuaria de Sevilla (APS) and Acuario de Sevilla for financial and 506 logistical support. This work was partially supported by the V Plan Propio Universidad 507 de Sevilla via two pre-doctoral grants (I. Donázar-Aramendía, J.M. Miro). Isotopic 508 analyses were carried out at the Laboratorio de Isótopos Estables of the Estación 509 Biológica de Doñana (LIE-EBD, Spain; www.ebd.csic.es/lie/index.html). We thank Dr. 510 Craig Layman for his invaluable help with stable isotope interpretation. 511 7. 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Impact vs Controls June 2015 I C Average dissimilarity: 44.52 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 21.96 35.48 2.43 2.38 5.46 Magelona papillicornis 16.02 7.66 1.78 1.57 4 Hyala vitrea 7.07 7.9 1.56 1.54 3.5 Sternaspis scutata 7.33 13.02 1.55 2.8 3.49 Spiophanes kroyeri 11.39 2.47 1.52 1.62 3.41 Eudorella truncatula 17.11 9.2 1.5 2.31 3.37 Sigambra parva 11.94 3.84 1.44 1.86 3.23 Medicorophium runcicorne 7.58 5.55 1.05 3.26 2.35 Capitella capitata 7.49 9.88 1.04 1.26 2.33 Medicorophium aculeatum 4.3 2.15 1.01 0.77 2.28 Nephtys hombergii 11.21 6.73 0.8 0.97 1.8 Iphinoe tenella 4 0 0.79 2.21 1.76 Bodotria scorpioides 4.55 0 0.75 1.17 1.69 Glycera tesselata 5.76 1.65 0.75 1.8 1.69 Nassarius incrassatus 3.84 0 0.72 3.86 1.61 Microspio mecznikowianus 7.95 4.47 0.7 1.47 1.57 Upogebia tipica 3.8 0 0.69 5.3 1.56 Nemerteao 13.34 9.67 0.69 1.64 1.56 Aonides oxycephala 8.19 4.79 0.67 1.65 1.49 Oestergrenia digitata 4.32 4.56 0.65 1.67 1.47 Cheirocratus sundevalli 1.72 3.29 0.59 1.26 1.34 Impact vs Controls July 2015 I C Average dissimilarity: 36.66 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 30.66 38.92 2.02 1.23 5.5 Magelona papillicornis 13.67 7.77 1.38 1.61 3.77 Spiophanes kroyeri 7.95 1.47 1.34 2.72 3.66 Hyala vitrea 8.25 11.48 1.3 1.57 3.53 Nephtys hombergii 11.37 5.71 1.24 1.44 3.39 Lumbrineris latreilli 15.08 12.2 1.13 1.46 3.09 Eudorella truncatula 9.69 4.61 1.06 1.93 2.88 Sigambra parva 8.27 3.27 1.03 1.84 2.82 Medicorophium runcicorne 7.24 2.33 1.01 1.36 2.75 Glycera tesselata 5.49 1.29 0.89 2.67 2.42 Spisula subtruncata 4.55 0 0.86 0.69 2.36 Corbula gibba 11.19 7.11 0.86 1.49 2.34 Mysia undata 3.8 0 0.79 5.04 2.16 Phoronida 5.79 2.21 0.78 1.37 2.14 Sternaspis scutata 7.28 10.2 0.75 1.24 2.05 Nucula hanleyi 8.48 6.59 0.72 1.55 1.96 Turritella turbona 4.2 0.86 0.71 2.52 1.94 Urothoe grimaldii 3.33 0 0.69 1.32 1.88 Impact vs Controls October 2015 I C Average dissimilarity: 31.49 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 48.98 71.95 4.28 1.36 13.59 Capitella capitata 3.93 13.35 1.71 2.32 5.43 Nephtys hombergii 11.6 6.33 0.96 1.14 3.06 Hemilepton nitidum 6.05 10.69 0.95 1.36 3.03 Upogebia tipica 11.94 10.46 0.88 1.23 2.79 Eudorella truncatula 3.93 8.32 0.87 1.42 2.78 Hyala vitrea 6.24 10.08 0.86 1.32 2.75 Lumbrineris latreilli 13.12 15.29 0.86 1.54 2.74 Sternaspis scutata 10.13 11.22 0.8 1.46 2.54 Phoronida 4.54 0.43 0.74 2.6 2.35 Corbula gibba 10.64 6.79 0.7 2.05 2.24 Upogebia deltaura 2.35 6.03 0.67 1.66 2.14 Turritella turbona 6.74 3.27 0.65 1.38 2.07 Chamelea gallina 3.44 0 0.63 2.64 1.99 Neanthes fucata 4.28 0.86 0.62 1.81 1.98 Impact vs Controls March 2016 I C Average dissimilarity: 44.00 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Hemilepton nitidum 12.64 0.61 2.92 1.22 6.63 Upogebia tipica 12.84 1.67 2.88 1.34 6.53 Apseudopsis latreillii 21.73 28.68 2.59 1.78 5.88 Magelona papillicornis 10.99 7.1 1.98 2.06 4.49 Capitella capitata 6.44 13.48 1.82 1.53 4.14 Terebellides stroemii 0 6.71 1.55 5.04 3.51 Medicorophium runcicorne 7.61 1.9 1.33 2.12 3.01 Corbula gibba 8.16 3.43 1.1 1.91 2.51 Hyala vitrea 6.9 9.75 1.01 1.26 2.29 Amphiura chiajei 6.31 2.04 0.99 2.4 2.25 Urothoe grimaldii 4.7 0.43 0.99 3.92 2.24 Aonides oxycephala 11.19 7.2 0.94 1.97 2.14 Aricidea catherinae 1.72 5.1 0.87 1.67 1.98 Lagis koreni 3.65 0 0.84 15.35 1.91 Eudorella truncatula 9.06 6.91 0.78 1.37 1.78 Impact vs Controls August 2016 I C Average dissimilarity: 42.01 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 21.5 19.9 2.07 1.24 4.92 Corbula gibba 17.95 8.56 2.06 1.45 4.9 Magelona papillicornis 13.67 5.92 1.66 1.63 3.95 Aonides oxycephala 12.16 5.2 1.42 1.73 3.37 Nephtys hombergii 13.82 8.19 1.15 1.32 2.73 Eudorella truncatula 8.47 3.4 1.14 1.75 2.72 Spiophanes kroyeri 5.83 0.43 1.08 1.53 2.57 Hyala vitrea 10.01 11.45 1.05 1.46 2.5 Photis longicaudata 5.26 0.43 1.03 3.7 2.44 Lumbrineris latreilli 15.44 14.86 0.98 1.42 2.34 Medicorophium aculeatum 3.44 1.67 0.93 0.77 2.21 Glycera tesselata 8.07 3.47 0.91 1.4 2.16 Urothoe grimaldii 4.39 0.43 0.87 1.39 2.07 Phoronida 5.07 1.04 0.87 1.73 2.06 Thracia phaseolina 4.13 0 0.75 0.69 1.79 Nucula hanleyi 8.2 6.67 0.73 2.1 1.75 Phaxas pellucidus 3.65 0 0.73 1.36 1.75 Tellina cf. compressa 3.72 0 0.71 1.07 1.69 Capitella capitata 12.9 15.92 0.69 1.2 1.65 Cossura soyeri 2.94 0 0.68 1.33 1.62 769 770 Table S2. Average abundance (Av. Abund.) of the most relevant species over the 771 sampling dates of samples in the control areas. Species are listed in decreasing order 772 according to their contribution to the average of the dissimilarity (Av. Diss.) between 773 areas until 50% of the accumulated total similarity. June vs July 2015 Jun Jul Average dissimilarity: 30.25 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 35.48 38.92 1.55 1.23 5.12 Hyala vitrea 7.9 11.48 1.43 1.18 4.71 Upogebia tipica 0 5.06 1.28 4.39 4.22 Eudorella truncatula 9.2 4.61 1.16 1.55 3.85 Capitella capitata 9.88 8.02 0.92 1.25 3.05 Ampelisca diadema 5.28 2.51 0.9 2.3 2.97 Hemilepton nitidum 0 3.53 0.89 1.72 2.94 Sternaspis scutata 13.02 10.2 0.86 1.49 2.84 Medicorophium runcicorne 5.55 2.33 0.8 1.96 2.66 Kurtiella bidentata 0 2.82 0.7 1.35 2.33 Magelona papillicornis 7.66 7.77 0.69 1.23 2.28 Microspio mecznikowianus 4.47 2.35 0.69 1.32 2.28 Nucula hanleyi 4.41 6.59 0.68 1.4 2.24 Turritella turbona 2.92 0.86 0.67 1.36 2.2 Cheirocratus sundevalli 3.29 2.64 0.65 1.36 2.16 Nemertea 9.67 7.44 0.64 1.49 2.11 Aonides oxycephala 4.79 2.51 0.62 1.26 2.06 June vs October 2015 Jun Oct Average dissimilarity: 36.15 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 35.48 71.95 7.46 4.53 20.64 Hemilepton nitidum 0 10.69 2.17 2.57 5.99 Upogebia tipica 0 10.46 2.11 1.81 5.83 Aonides oxycephala 4.79 11.28 1.33 1.99 3.68 Hyala vitrea 7.9 10.08 1.1 1.33 3.03 Nucula hanleyi 4.41 9.66 1.07 2.07 2.95 Leucothoe incisa 1.47 6.4 1.01 2.21 2.8 Capitella capitata 9.88 13.35 0.91 1.61 2.52 Ampelisca diadema 5.28 1.18 0.9 1.84 2.49 Sternaspis scutata 13.02 11.22 0.63 1.61 1.75 July vs October 2015 Jul Oct Average dissimilarity: 33.27 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 38.92 71.95 7.05 3.84 21.18 Aonides oxycephala 2.51 11.28 1.86 3.05 5.6 Hemilepton nitidum 3.53 10.69 1.53 1.63 4.61 Upogebia tipica 5.06 10.46 1.32 1.29 3.98 Capitella capitata 8.02 13.35 1.26 2.02 3.8 Leucothoe incisa 1.9 6.4 0.95 2.16 2.86 Hyala vitrea 11.48 10.08 0.9 1.19 2.71 Eudorella truncatula 4.61 8.32 0.84 1.57 2.52 Upogebia deltaura 2.26 6.03 0.79 1.65 2.38 Nucula hanleyi 6.59 9.66 0.74 1.44 2.23 October 2015 vs March 2016 Oct Mar Average dissimilarity: 37.58 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 71.95 28.68 9.29 5.73 24.71 Hemilepton nitidum 10.69 0.61 2.14 2.34 5.69 Upogebia tipica 10.46 1.67 2.03 1.6 5.39 Upogebia deltaura 6.03 0 1.28 4.04 3.42 Sternaspis scutata 11.22 5.39 1.27 1.73 3.37 Leucothoe incisa 6.4 1.35 1.09 2.02 2.9 Hyala vitrea 10.08 9.75 1.01 1.39 2.68 Terebellides stroemii 2.21 6.71 0.97 2.04 2.59 March 2016 vs August 2016 Mar Aug Average dissimilarity: 31.96 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 28.68 19.9 2.67 1.41 8.34 Hyala vitrea 9.75 11.45 1.48 1.37 4.62 Corbula gibba 3.43 8.56 1.47 1.8 4.59 Terebellides stroemii 6.71 1.65 1.45 2.13 4.52 Eudorella truncatula 6.91 3.4 1.05 1.17 3.3 Kurtiella bidentata 0.61 4.15 1.05 1.31 3.27 Spiophanes kroyeri 3.82 0.43 0.97 1.4 3.02 Lumbrineris latreilli 12.96 14.86 0.93 1.44 2.9 Capitella capitata 13.48 15.92 0.92 1.22 2.88 Ampelisca diadema 2.76 5.71 0.82 1.4 2.58 Magelona papillicornis 7.1 5.92 0.81 1.14 2.54 Venus casina 0.43 3.08 0.77 1.7 2.41 Spiochaetopterus costarum 0.43 3.12 0.77 1.73 2.4 Upogebia tipica 1.67 1.92 0.76 0.8 2.39 774 Turritella turbona 2.82 0.43 0.75 1.34 2.33 775 Table S3. Average abundance (Av. Abund.) of the most relevant species over the 776 sampling dates of samples in the disposal area. Species are listed in decreasing order 777 according to their contribution to the average of the dissimilarity (Av. Diss.) between 778 areas until 50% of the accumulated total similarity. June vs July 2015 Jun Jul Average dissimilarity: 41.20 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 21.96 30.66 2.01 2.02 4.87 Magelona papillicornis 16.02 13.67 1.45 1.55 3.53 Hyala vitrea 7.07 8.25 1.45 1.63 3.52 Eudorella truncatula 17.11 9.69 1.25 2.3 3.04 Sternaspis scutata 7.33 7.28 1.2 1.76 2.92 Nephtys hombergii 11.21 11.37 1 1.55 2.44 Phoronida 0 5.79 0.96 2.49 2.32 Medicorophium runcicorne 7.58 7.24 0.95 1.51 2.3 Sigambra parva 11.94 8.27 0.83 1.76 2.02 Spisula subtruncata 2.72 4.55 0.83 0.89 2.02 Lumbrineris latreilli 14.2 15.08 0.8 1.58 1.94 Medicorophium aculeatum 4.3 0 0.8 0.66 1.93 Capitella capitata 7.49 7.88 0.79 1.57 1.92 Spiophanes kroyeri 11.39 7.95 0.79 0.98 1.91 Hemilepton nitidum 0 4.35 0.72 2.15 1.75 Iphinoe tenella 4 0 0.69 2.18 1.67 Bodotria scorpioides 4.55 0 0.67 1.12 1.63 Aonides oxycephala 8.19 4.07 0.64 2.05 1.56 Oestergrenia digitata 4.32 2.35 0.64 1.2 1.54 Nemertea 13.34 9.87 0.63 1.55 1.53 Nassarius incrassatus 3.84 2.43 0.62 3.32 1.5 Ampelisca diadema 6.14 3.94 0.61 1.26 1.48 Nucula hanleyi 5.49 8.48 0.61 1.48 1.48 June vs October 2015 Jun Oct Average dissimilarity: 45.93 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 21.96 48.98 4.41 1.46 9.61 Eudorella truncatula 17.11 3.93 2.22 3.48 4.84 Magelona papillicornis 16.02 9.55 1.53 1.75 3.32 Upogebia tipica 3.8 11.94 1.39 3.4 3.03 Sternaspis scutata 7.33 10.13 1.27 1.54 2.76 Hyala vitrea 7.07 6.24 1.26 1.5 2.74 Spiophanes kroyeri 11.39 4.36 1.09 1.07 2.37 Medicorophium runcicorne 7.58 2.35 1.08 1.84 2.34 Hemilepton nitidum 0 6.05 1.02 2.92 2.21 Capitella capitata 7.49 3.93 1 1.65 2.18 Sigambra parva 11.94 6.35 0.95 1.65 2.07 Nephtys hombergii 11.21 11.6 0.92 1.2 2.01 Nemertea 13.34 8.01 0.9 2.19 1.95 Medicorophium aculeatum 4.3 0 0.81 0.67 1.76 Lumbrineris latreilli 14.2 13.12 0.79 1.67 1.71 Nucula hanleyi 5.49 9.99 0.78 2.89 1.69 Phoronida 0 4.54 0.76 3.19 1.66 Neanthes fucata 0 4.28 0.72 2.77 1.57 Iphinoe tenella 4 0 0.7 2.21 1.52 July vs October 2015 Jul Oct Average dissimilarity: 34.28 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 30.66 48.98 3.89 1.47 11.34 Upogebia tipica 4.07 11.94 1.45 2.09 4.24 Lumbrineris latreilli 15.08 13.12 1.15 1.38 3.34 Hyala vitrea 8.25 6.24 1.13 2.38 3.29 Eudorella truncatula 9.69 3.93 1.02 1.45 2.99 Nephtys hombergii 11.37 11.6 0.99 1.35 2.9 Magelona papillicornis 13.67 9.55 0.94 1.83 2.73 Medicorophium runcicorne 7.24 2.35 0.92 1.48 2.68 Aonides oxycephala 4.07 9.1 0.91 2.21 2.64 Sternaspis scutata 7.28 10.13 0.9 1.38 2.63 Spisula subtruncata 4.55 0.86 0.81 0.82 2.37 Capitella capitata 7.88 3.93 0.73 1.2 2.14 Spiophanes kroyeri 7.95 4.36 0.71 1.13 2.07 Mysia undata 3.8 0 0.68 4.66 1.98 Abra nitida 3.21 3.14 0.56 1.52 1.63 Ampelisca diadema 3.94 3.21 0.55 1.72 1.59 October 2015 vs March 2016 Oct Mar Average dissimilarity: 38.99 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Apseudopsis latreillii 48.98 21.73 5.47 1.54 14.02 Hemilepton nitidum 6.05 12.64 2.07 1.58 5.31 Upogebia tipica 11.94 12.84 1.71 2.61 4.38 Magelona papillicornis 9.55 10.99 1.5 1.73 3.86 Capitella capitata 3.93 6.44 1.07 1.24 2.74 Eudorella truncatula 3.93 9.06 1.03 1.48 2.65 Sternaspis scutata 10.13 5.56 1.03 1.2 2.65 Medicorophium runcicorne 2.35 7.61 1 2.2 2.56 Lumbrineris latreilli 13.12 14.05 0.93 1.42 2.38 Nephtys hombergii 11.6 8.79 0.9 1.2 2.31 Sigambra parva 6.35 3.44 0.74 1.49 1.89 Chamelea gallina 3.44 0 0.66 2.56 1.7 Neanthes fucata 4.28 0.86 0.66 1.76 1.7 Nemertea 8.01 5.8 0.63 1.42 1.62 Leucothoe incisa 4.7 3.14 0.57 2.29 1.46 March 2016 vs August 2016 Mar Aug Average dissimilarity: 43.87 Species Av.Abund Av.Abund Av.Diss Diss/SD Contrib% Upogebia tipica 12.84 0.86 2.34 1.37 5.33 Hemilepton nitidum 12.64 3.65 2.17 1.12 4.96 Apseudopsis latreillii 21.73 21.5 2.02 1.14 4.61 Corbula gibba 8.16 17.95 1.77 1.34 4.03 Magelona papillicornis 10.99 13.67 1.56 1.56 3.56 Capitella capitata 6.44 12.9 1.39 1.39 3.17 Nephtys hombergii 8.79 13.82 0.97 1.18 2.21 Photis longicaudata 0 5.26 0.95 8.51 2.17 Aricidea catherinae 1.72 6.75 0.94 1.72 2.15 Hyala vitrea 6.9 10.01 0.93 1.7 2.12 Medicorophium runcicorne 7.61 3.44 0.91 1.46 2.07 Lumbrineris latreilli 14.05 15.44 0.86 1.49 1.96 Venus casina 1.22 5.37 0.78 1.97 1.78 Sigambra parva 3.44 6.85 0.78 1.49 1.78 Turritella turbona 4.16 0 0.77 5.02 1.75 Thracia phaseolina 0.86 4.13 0.73 0.83 1.65 Medicorophium aculeatum 0 3.44 0.71 0.67 1.61 Spiophanes kroyeri 6.48 5.83 0.7 4.35 1.6 779 Spisula subtruncata 1.72 3.33 0.67 1.23 1.53