Taxonomic and functional patterns of macrobenthic communities on a high-Arctic shelf: A case study from the Laptev Sea

Accepted Manuscript Taxonomic and functional patterns of macrobenthic communities on a high-Arctic shelf: A case study from the Laptev Sea

V.N. Kokarev, A.A. Vedenin, A.B. Basin, A.I. Azovsky PII: DOI: Reference:

S1385-1101(17)30113-2 doi: 10.1016/j.seares.2017.08.011 SEARES 1593

To appear in:

Journal of Sea Research

Received date: Revised date: Accepted date:

23 April 2017 19 August 2017 23 August 2017

Please cite this article as: V.N. Kokarev, A.A. Vedenin, A.B. Basin, A.I. Azovsky , Taxonomic and functional patterns of macrobenthic communities on a high-Arctic shelf: A case study from the Laptev Sea, Journal of Sea Research (2017), doi: 10.1016/ j.seares.2017.08.011

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ACCEPTED MANUSCRIPT Taxonomic and functional patterns of macrobenthic communities on a high-Arctic shelf: a case study from the Laptev Sea V. N. Kokarev1,2*, A. A. Vedenin2, A. B. Basin2, A. I. Azovsky1,2 *e-mail: [email protected] 1

M. V. Lomonosov Moscow State University, Faculty of Biology, Leninskie Gory 1/12,119234 Moscow, Russia

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P. P. Shirshov Institute of Oceanology, Russian Academy of Sciences, Nakhimovsky Prospect 36, 117997 Moscow,

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Abstract

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The studies of functional structure of high-Arctic Ecosystems are scarce. We used data on benthic macrofauna from 500-km latitudinal transect in the eastern Laptev Sea, from the Lena delta to the continental shelf break, to describe spatial patterns in species composition, taxonomic and functional structure in relation to environmental factors. Both taxonomy-based approach and Biological Trait analysis yielded similar results and showed general depthrelated gradient in benthic diversity and composition. This congruence between taxonomical and functional dimensions of community organization suggests that the same environmental factors (primarily riverine input and regime of sedimentation) have similar effect on both community structure and functioning. BTA also revealed a distinct functional structure of stations situated at the Eastern Lena valley, with dominance of motile, burrowing subsurface deposit-feeders and absence of sedentary tube-dwelling forms. The overall spatial distribution of benthic assemblages corresponds well to that described there in preceding decades, evidencing the long-term stability of bottom ecosystem. Strong linear relationship between species and traits diversity, however, indicates low functional redundancy, which potentially makes the ecosystem susceptible to a species loss or structural shifts.

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Keywords: Laptev Sea; Macrozoobenthos; Biologial Trait Analysis (BTA); Functional structure; Diversity; Redundancy

ACCEPTED MANUSCRIPT 2 1.

Introduction

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The Laptev Sea is a Siberian epicontinental sea located between the Taimyr Peninsula in the west and the New Siberian Islands in the east. It is relatively shallow with a shelf break occurring at 50 to 60 m depth (Holmes and Creager, 1974). The hydrological regime is highly influenced by river runoff, especially originating from the Lena River, and long-lasting sea-ice cover with recurring polynyas (Timokhov, 1994). Moreover, the river discharge is a significant source of the organic carbon found in surface sediments (Fahl and Stein, 1997; Xiao et al., 2013). Highly complex geomorphology, diverse currents and sedimentation patterns in the Laptev Sea result in a clear bathymetric zonation of the benthic macrofauna (Petryashov et al., 2004; Steffens et al., 2006). However, the current knowledge on macrobenthic distribution patterns is based on investigations conducted more than a decade ago, and those studies did not consider functional aspects related to the biological traits of the species.

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Understanding the relationship between biodiversity and ecosystem functioning in marine environment is a challenging task (Strong et al., 2015). To link species composition to function, Biological trait analysis (BTA) has been recently applied to describe marine macrobenthic communities (Bremner et al., 2006). It is proposed as a powerful tool to describe community patterns in a changing environment (Bremner, 2008). BTA has been proved suitable to describe functional changes in response to human-induced disturbance (e.g., Tillin et al., 2006; Cooper et al., 2008; Oug et al., 2012; Bolam et al., 2016) and environmental gradients (e.g., Paganelli et al., 2012; van der Linden, 2012). In general, species-rich communities are perceived as being more robust in maintaining ecological function in a changing environment (Loreau et al., 2001). High functional redundancy is treated as an insurance policy against the loss of function due to a species loss (Loreau et al., 2001; van der Linden, 2012). However, some benthic communities still maintain high functional diversity at a low species number (Micheli and Halpern, 2005; Törnroos et al., 2015). Regulation of ecosystem functions and corresponding structural features may be strongly influenced by species-specific traits rather than by species richness per se (Loreau et al., 2001; Hooper et al., 2005). On the other hand, comparisons between functional and taxonomical composition of natural communities yielded disparate results, varying from strong (e.g., Kalogeropoulou et al., 2015; Bolam et al., 2016) to weak (e.g., Cochrane et al., 2012; Frid and Caswell, 2015) congruence between these two dimensions. Similarly, species diversity–functional diversity relationship changed across different habitats, taxa and/or size classes (Hooper et al., 2005; Paganelli et al., 2012; and literature therein). In this way, we intended to test the correspondence between two different approaches to community description (taxonomic and functional).

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Although the number of papers using BTA is increasing (Beauchard et al., 2017), the majority of studies on macrobenthic traits composition have been conducted in temperate seas while comparable investigations on Arctic macrobenthic communities are almost absent. Considering that global climate change and increasing human activities can significantly alter high-latitude ecosystems with consequences unknown (Bluhm et al., 2011; Wassman et al., 2011) data on the functional structure of Arctic macrobenthos are of a particular interest. Expected changes in species distributions and altered patterns of primary and secondary production would affect the trait composition of benthic assemblages and, consequently, ecosystem functioning. Therefore, there is strong need in collecting data on Arctic benthos traits and the factors affecting its distribution. We used data on benthic macrofauna from 500-km latitudinal transect across the Lena Delta area (the eastern Laptev Sea) to 1) describe spatial patterns in species composition, taxonomic and functional structure in relation to environmental factors, 2) evaluate the functional redundancy and spatial congruence between taxonomic, phylogenetic and functional diversity, and 3) compare the distribution of benthic assemblages at present and in preceding decades.

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Materials and methods

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3 2.1. Study area. The investigation took place in the eastern Laptev Sea during the 63d cruise of R/V “Akademik Mstislav Keldysh” in September 2015. Samples were collected along the 130.5° E latitudinal transect (500 km long) at water depths of 10 to 91 m (Table 1). The shallowest stations were located near the Lena delta while the deepest one bordered the continental slope (Fig. 1). Several environmental variables were recorded at each station: bottom-water salinity (psu) and temperature (°C), bottom-water oxygen saturation (%), % of mud fraction (particle size < 0.05 mm) and % of total organic carbon in the upper 5 cm of the sediment (Table 1). No sedimentological data were available for the shallowest stations (5216, 5217).

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Figure 1. Laptev sea. Map showing location of macrobenthic sampling stations visited in September 2015. The 100-m and 1000-m water depth contours are shown.

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Table 1. List of stations where macrobenthic samples have been collected in the Laptev Sea during 63d cruise of R/V "Akademik Mstislav Keldysh" in September 2015. n/a – data not available. Water depth (m)

Bottomwater T (°C)

Bottomwater salinity

Bottom - water O2 (%)

Mud content (%)

Total Organic Carbon (%)

130.105

10

-0.19

29.405

91.4

n/a

n/a

72.400

130.500

14

-0.15

28.858

64.3

n/a

n/a

08.09.2015

72.683

130.500

18

-0.47

31.108

68.1

86.71

3.23

08.09.2015

73.330

130.490

25

-0.64

31.565

83.0

79.51

1.53

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Date

Latitude (°N)

Longitude (°E)

5216

07.09.2015

71.997

5217

07.09.2015

5218 5220

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74.250

130.498

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-1.60

33.854

65.9

35.49

0.51

5221

09.09.2015

74.917

130.413

37

-1.75

34.324

66.7

79.67

1.71

5222

09.09.2015

75.808

130.496

49

-1.75

33.983

75.1

74.19

1.57

5223

10.09.2015

76.470

130.500

59

-1.73

33.853

89.1

85.17

1.38

5224

10.09.2015

77.100

130.488

62

-1.51

34.003

73.4

70.59

0.76

5228

13.09.2015

77.638

130.498

89

-1.11

34.468

62.66

0.74

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84.5

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2.2. Sampling and sample processing. An “Ocean-0.1” grab with an opening of 0.1 m² was used for macrofauna sampling. Three replicates were taken at each station. The sediment in the grab was sieved on a 0.5-mm mesh, and the sieve residue was fixed in 6% buffered formalin diluted in sea water. In the lab, animals were sorted from the replicate sediment samples under a stereomicroscope, identified to species level wherever possible, counted and weighed with an accuracy of 0.001 g. Subsequent analyses of taxonomic and functional structure were performed using the abundance and biomass values averaged across the three replicates per station, while diversity measures were calculated on pooled abundance data for three replicates.

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The upper 5 cm of sediments were sampled with a Niemistö gravity corer. Granulometry of these samples was analyzed using a laser granulometer «Analizeter-22». Total organic carbon was determined using the dichromate oxidation method. Data on bottom-water salinity and temperature were made available by S. A. Shchuka (IO RAS), and data on bottom-water oxygen saturation were provided by A. A. Polukhin (IO RAS).

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2.3. Taxonomic composition. Species abundances and biomasses were combined into a species’ respiration rates R estimated as:

R  k N 0.25 B 0.75

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where N is the abundance of a species, B is biomass, and k is a taxon-specific coefficient (after Jirkov, 2010: 0.74 for Errantia Polychaeta; 0.69 for Crustacea; 0.5 for Bivalvia, Sedentaria Polychaeta, Nemertini, Priapulida, Sipunculida and Aplacophora; 0.81 for Oligochaeta; 0.42 for Gastropoda; 0.15 for Echinodermata; 0.14 for Bryozoa; 0.1 for Alcyonaria and Actinaria). As this measure combines both abundance and biomass of each species, it ensures a balanced contribution of small but abundant species and of large ones with low abundance but high biomass (Azovsky et al., 2000; Vedenin et al., 2015). Prior to analysis, respiration values were standardized station-wise and subsequently square-root transformed to reduce the role of dominant species, as proposed by Clarke and Warwick (2001). The Bray-Curtis similarities between stations were calculated using transformed R values. To emphasize the purely “taxonomic” aspect of the community composition, we also used the taxonomic dissimilarity measure Gamma+, which is a derivative of the Bray-Curtis similarity computed with presence/absence data but taking into consideration the taxonomic relationships between the species (Clarke et al., 2006). The following levels of taxonomy were used: phylum, class, order, family, genus and species. For polychaetes, the following clades were used as orders (Rouse and Fauchald, 1997): Scolecida, Eunicida, Phyllodocida, Sabellida, Spionida, and Terebellida. To assess the community structure, we performed Multidimensional scaling (MDS) based on both Bray-Curtis and Gamma+ resemblance matrices. The MDS ordination was carried out using the Primer 6 software.

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5 2.4. Diversity indexes. Total species number, expected number of species per 100 individuals (ES 100) and Shannon index (to a log base of 2) were used as measures of species diversity. In addition, average taxonomic distinctness (Δ*) (Clarke and Warwick, 2001) was computed. Functional diversity (FD) was estimated by Rao’s quadratic entropy, which is commonly used in trait-based marine benthic studies. It was calculated using the software “FunctDiv.xls” (http://botanika.bf.jcu.cz/suspa/FunctDiv.php; Lepš et al., 2006). FD indexes were calculated separately for each trait and summed up per station. Correlations among indices were tested with a Pearson correlation test. To assess the relationship between taxonomic and functional diversity, two approaches were applied. First, we used the the functional redundancy index as the ratio between functional diversity index and Shannon index (FD/H’ ratio) (Van der Linden et al., 2012). When this ratio decreases, functional redundancy (number of species exhibiting the same trait) increases. We also made the linear regression of FD on H’. The strong relationship with slope close to 1 indicates low redundancy (each species plays a unique functional role), whereas slope close to zero indicates high redundancy (multiple species have similar functional traits) (Micheli and Halpern, 2005).

Position in sediments Mobility

Living Habit

Feeding Habit

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Body design

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Maximum adult size

Modality <1cm 1-3cm 3-5cm >5cm Vermiworm, segmented Vermiworm, unsegmented Bivalved Turbinate Articulate Radial Colonial Epifauna Infauna Mobile Discretely mobile Sessile Tube-dweller Burrower Surface crawler/swimmer Attached Surface-deposit feeder Subsurface-deposit

Code S1 S2 S3 S4 BD1 BD2

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Table 2. List of biological traits and their modalities.

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2.5. Biological trait analysis. One of the most important steps in BTA is choosing traits (Bremner et al, 2006). We used seven biological traits, subdivided into 28 modalities, reflecting various life-style properties of benthic softbottom invertebrates (Table 2). Species were assigned to traits using a fuzzy coding approach (Chevenet et al., 1994) based on information found in the literature (see the Electronic Supplement for the references). In case of missing data, zero scores were assigned for each modality. Although the trait “Reproduction strategy” contained the data for only 2/3 of all taxa, we still included it in the analysis, since the missing values reflected the gaps in knowledge of life history traits of rarely encountered species.

BD3 BD4 BD5 BD6 BD7 P1 P2 M1 M2 M3 LH1 LH2 LH3 LH4 FH1 FH2

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6 feeder Carnivore/Omnivore FH3 Suspension feeder FH4 Symbiont FH5 Pelagic RS1 Reproduction Short-pelagic RS2 strategy Benthic RS3 To assess functional structure, the values in the “Trait x Species” table should be weighted by a measure of species importance in the community. Biomass and abundance are the most routinely used metrics. However, as with taxonomic structure, they both have their own disadvantages. In this study, we used respiration rate (see above). Before weighting, the species respiration rates were square root transformed in order to reduce the role of dominant species. The weighting procedure was carried out by multiplying species scores from the “Trait x Species” matrix by the corresponding values in the “Species x Respiration“ matrix. These products were stored in a “Traits x Station” matrix and standardized for each trait. Fuzzy Correspondence Analysis (FCA) available in the R package ade4 (R version 3.2.0; ade4 ver. 1.7-2) was used to distinguish the traits that contribute most to the differences between stations (Bremner et al., 2006).

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Correlation-based Principal Component Analysis (PCA) was used to reveal trends in environmental variables along the transect. Missing values from stations 5216 and 6217 are replaced by regression values estimated by iterative imputation procedure (Hammer et al., 2001). The pair-wise environmental differences between stations were estimated as Euclidean distances between scores at two first components’ space. To evaluate correspondence among the ordination of stations by environmental conditions, taxonomical and functional structure, pair-wise Mantel test was performed for the resemblance/distance matrices.

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3.1. Environmental variables. The PCA based on environmental data (Fig. 2) showed that the first component accounted for 66.9% of the total variation and reflected the general along-transect trend from shallow, warm, brackish-water stations with sediments enriched by total organic carbon (right, stations 5216, 5217, 5218 and 5220) to deeper, cold and saline waters with lower organic content (left, stations 5221-5228). The second component accounted for 21.9% of the total variation and correlated mainly with oxygen content.

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Figure 2. Principal Component Analysis based on the environmental factors (Depth, Sal - salinity, Temp - temperature, O2 oxygen saturation, Mud – mud content, Corg – total organic carbon content). PC1 explained 66.9 % of total variation, PC2 – 21.9%.

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3.2. Univariate characteristics. Overall, 197 species were recorded in the samples, with Polychaeta, Crustacea and Bivalvia being the most species-rich taxa (78, 44, and 28 species, respectively). Abundance was lowest both at the shallowest stations located near the Lena delta and at the deepest part (Fig. 3A). Biomass showed no clear depthrelated pattern with stations 5217 and 5228 having the lowest values (Fig. 3B). Most of taxonomic and functional diversity indexes showed coincident increasing trends with depth. The only exception is the average taxonomic distinctness Δ* (Fig. 3F), which generally decreased with depth, due to increasing number of taxonomically related species while number of higher taxa remained constant. The two stations 5221 and 5222 stood out against the general trend, showing a significant decrease in all diversity indexes compared to the nearby stations. Functional diversity (FD) was closely correlated with species diversity indices (species number, S: r = 0.94; ES(100): r = 0.94; H’ : r = 0.96; all correlations significant at p < 0.01). The lowest functional redundancy (FD/H’ values = 0.85-1.00) were observed on the stations close to the Lena Delta. All other stations had a similar level of redundancy (mean FD/H’ value = 0.75), despite the pronounced variation in species number (Fig. 3H). Functional diversity increased in direct proportion to the taxonomic one (Fig. 3I; slope = 0.78).

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ACCEPTED MANUSCRIPT 9 Figure 3. Macrofaunal characteristics: A - total abundance, ind/0.1 m2; B - total biomass, g/0.1 m2; C – species number, S; D expected number of species per 100 individuals, ES (100); E - Shannon’ diversity index, H’; F - average taxonomic distinctness, Δ*; G - functional diversity, FD; H - functional redundancy, FD/H’; I – relationship between FD and H’ values. At graphs A-H, stations listed from left to right in order of increasing depth.

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3.3. Taxonomic structure. Ordinations based on the macrobenthic taxonomic resemblances among the stations revealed a clear depth-related pattern, irrespective of whether species similarities (Fig. 4) or Gamma+ dissimilarities (Fig. 5) were analyzed. The two shallowest stations 5216 and 5217, dominated by the bivalve Portlandia aestuariorum (Fig. 6), were clearly different from all the other transect stations, while the taxonomic differences between the other stations were less pronounced (Figs. 4, 5). Stations 5218 and 5220 were dominated by the bivalve Portlandia arctica, with a few large bivalves Astarte borealis occurring at the latter one (Fig. 6). The bivalve Ennucula tenuis, the crustacean Byblis gaimardii and the polychaete Maldane sarsi were most abundant at station 5215/2, which was located at the same depth but further away from the Lena delta. At water depths from 30 to 50 m (Stations 5221 and 5222), the protobranchian bivalves Ennucula tenuis and Nuculana pernula, the opiuroid Ophiocten sericeum and the polychaetes Scalibregma inflatum, Capitella capitata and Aricidea nolani were the most abundant species. Oweniid and maldanid polychaetes (Myriochele heeri, Owenia polaris and Maldane sarsi) and the bivalve Bathyarca glacialis predominated at the deepest stations 5223 and 5224. The polychaetes Aglaophamus malmgreni, Spiochaetopterus typicus, Maldane arctica and Scoletoma fragilis contributed most to the macrofauna at station 5228 bordering the slope.

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Overall, there was a distinct shift from species-poor bivalve-dominated bottom macrofauna in shallow southern waters to species-rich, polychaete-dominated communities at the northern deeper part of the transect (Figs. 3-6).

Figure 4. Macrobenthos of the eastern Laptev Sea in September 2015. MDS ordination of stations, based on similarity in species composition quantified with Bray-Curtis values of square root-transformed data of relative respiration rates (Stress = 0.07).

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Figure 5. Macrobenthos of the eastern Laptev Sea in September 2015. MDS ordination of stations, based on dissimilarities in taxonomic composition quantified with Gamma+ indices computed with presence/absence data (Stress = 0.05).

Figure 6. Species that contribute ≥ 8% to the total macrobenthic respiration at at least one station. Size of square is proportional to a species contribution. In brackets: B - Bivalvia, C - Crustacea, O - Ophiuroidea, P - Polychaeta.

ACCEPTED MANUSCRIPT 11 3.4. Functional structure. Four biological traits (Maximum adult size, Body design, Living habit and Reproduction strategy) contributed most to the first axis of the Fuzzy Correspondence Analysis (FCA) ordination, which explained over a half of total functional variability (Table 3). Stations were mainly ordinated along a gradient following this axis, and their positions along this axis were highly correlated with latitude (r = 0.837) and depth (r = 0.771). The left part of the axis corresponded to the assemblage with prevalence of medium-sized (1-3 cm), bivalved burrowers with a short pelagic stage (Fig. 7B). This assemblage was found at the shallow stations (Fig. 7A: 5216, 5217, 5218, 5220, 5221, and 5222). Stations concentrated at the right end of the axis (Fig. 7A: 5215/2, 5223, 5224, and 5228) were more diverse in terms of these traits, with a significant contribution of large, sedentary, mainly tubedwelling organisms (Fig. 7B).

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The two traits, Feeding habit and Mobility, contributed most to the second FCA axis (Table 3). This axis accentuated the contrast between station 5220, characterized by a greater proportion of discretely mobile suspension feeders (mainly Astarte spp.) (Fig. 7B), and stations 5221 and 5222 (Fig. 7A), where motile, burrowing sub-surface deposit feeders (M1+FD2,Fig. 7B) (Scalibregma inflatum, Capitella capitata and Aricidea nolani) prevailed over the tubedwelling worms (M2+FH1+LH1). The positions of stations along this axis showed a relatively high (though not significant) negative correlation with oxygen concentrations (r = -0.493).

Body design

0.145

0.052

Position in sediments

0.012

0.006

Mobility

0.063

0.059

Living habit

0.086

0.040

Feeding habit

0.050

0.0810

Reproduction strategy

0.120

0.001

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F1 0.113

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Table 3. Correlation ratios of the biological traits used in this study with the two first axes of FCA. Bold figures indicate traits that contribute most (4 on the first axis and 2 on the second).

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Results of the Mantel tests (Table 4) showed that ordinations of stations based on species percentages, taxa composition and functional structure, corresponded well to each other and to the environmental differences described by the first PC component. Table 4. Results of Mantel test for match between resemblance/distance matrices (BC- Bray-Curtis similarity, Γ+ - taxonomic dissimilarity, BT – functional dissimilarity (Euclidean distance in two first FDA axes), ENV – environmental distance along first, second or both PC axes. Rho values (above diagonal, significant values in bold) and significance levels (under diagonal).

BC BC

Γ+

BT

ENV PC1

ENV PC2

ENV PC 1+2

0.852

0.575

0.706

0.080

0.723

0.750

0.590

0.025

0.582

0.399

0.075

0.406

Γ+

0.001

BT

0.001

0. 001

ENV PC1

0.002

0.005

0.019

ENV PC2

0.267

0.418

0.288

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0.030

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ENV PC 1+2

Figure 7. Ordination in first two FCA axes based on respiration-weighed traits composition: A) stations and B) traits. The first two axes explained 73.4% of the total variation in functional structure.

ACCEPTED MANUSCRIPT 13 Discussion

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4.1. Choice of traits. In BTA studies, the choice of traits is generally of particular importance. In this study, we have focused on traits related to biology and life style and, in contrast to some other studies, did not consider traits of environmental preferences (e.g. salinity preference; Van der Linden et al., 2012). Most traits used here were found useful to describe the observed patterns and contributed significantly in first two FDA axes, except for “Position in sediment”. That could be explained by the fact that grab samples underestimate the epifauna (Vedenin et al., 2015). Another problem is that the life-history patterns of Arctic macrofauna are still poorly known. We adopted the classification proposed by Fetzer and Arntz (2008), who classified reproduction strategies of Kara Sea species in terms of their larval-stage dispersal capabilities. The use of traits concerning morphological characteristics has recently been questioned (Beauchard et al., 2017); while the others suggest including as many traits as possible, in order to obtain more perfect description of ecological functioning (Bremner et al., 2006). We adopt the latter viewpoint, since different body morphology can result in different biological characteristics (e.g. ability to asexual reproduction and regeneration), as well as ecological preferences (e.g. absence of echinoderms in brackish waters). Thus, modalities of body designs can still serve as ecological indicators.

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4.2. Functional and taxonomic patterns. Our data reveal noticeable changes in diversity and composition of benthic macrofauna along the latitudinal transect, from relatively species-poor communities dominated by bivalves in the proximity to the Lena delta to more diverse and abundant fauna dominated by polychaetes and brittle stars in the northern part of the study area. The vicinity of a river delta obviously plays an important role in structuring benthic communities. The majority of the Lena river discharge (86%) enters the Laptev east of the Lena delta (Rachold et al., 1996), where the four shallowest stations (5216, 5217, 5218, 5220), dominated exclusively by Portlandia spp., were located. They are influenced not only by the inflow of polyhaline waters (18-30 psu; Stepanova et al., 2017), but also by sedimentation of terrigenous organic matter, which results in high total organic carbon content in the surface sediments (Fahl and Stein, 1997; Xiao et al., 2013). In general, Portlandia species are known to dominate in Arctic areas characterized by such environmental conditions (Vedenin et al., 2015; Galkin and Vedenin, 2015), as well in areas associated with glacial sedimentation (Syvitski et al., 1989; Wlodarska-Kowalszuk and Pearson, 2004). Station 5216 had a unique functional structure due to an extremely low number of species and a high dominance of Portlandia aestuariorum. Station 5217 was similar to 5218 in terms of trait composition but consisted of a more brackish-water fauna. On the contrary, station 5220 was characterized by lower organic carbon content, which indicates less sedimentation rates of riverine suspended matter, and a higher taxonomic and functional diversity with a greater proportion of suspension feeders. In general, this shallowest brackish-water area is occupied by relatively low-diverse assemblage of medium-sized, bivalved infauna with surface deposit or suspension feeding modes. Assemblages with similar profile of traits and functional diversity increasing seaward along a spatial gradient have been described in some other transitional (estuarine or delta) areas (Paganelli et al., 2012; van der Linden et al., 2012). Most probably the fluctuations in salinity and sedimentation of terrestrial particulate matter contribute to the instability of the environment that selects species with particular set of traits resulting in functional convergence. The deepest stations (5223, 5224 and 5228) are under the influence of cold, euhaline (32–34 psu) Arctic waters, as indicated by the comparatively high abundances of polychaetes and echinoderms. These stations grouped together along the first FCA axis, being more diverse than the southern, shallow stations, and characterized by the prevalence of discretely mobile and sessile, attached or tube-dwelling forms. In general, communities dominated by tubedwelling polychaetes are common on Arctic shelves (Cochrane et al., 2009; 2012). Tube-dwelling organisms can have a significant effect on sediment stability and biogeochemistry (Jirkov, 2010). It appears that this functionally important forms mark the sediments not prone to enhanced sedimentation and strong bottom currents (WlodarskaKowalszuk and Pearson, 2004). The station 5215/2, which is situated shallower and further south along the transect, also groups with these stations in terms of its functional structure, while comparison based on taxonomic dissimilarity revealed a different species

ACCEPTED MANUSCRIPT 14 composition. This is in accordance with previous investigations that found trait composition to be affected by local-scale habitat variation rather than large-scale processes and available pool of species (Bremner et al., 2006; Hewitt et al., 2008). The high total abundance (6,437 ind m-2) recorded at the station 5215/2 is likely linked to a peculiar hydrological conditions at this station, which result in the local maximum of phytoplankton biomass (Suhanova et al., 2017), providing the input of fresh organic matter to the bottom. This is supported by the fact that more than half of total macrobenthic abundance at this station was represented by suspension- and surface depositfeeders, such as amphipod Byblis gaimardii, cumaceans and cirratulid polychaets.

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The second FCA axis accentuates the distinct position of stations 5221 and 5222, which also have noticeably low taxonomical and functional diversity (Fig. 3, 5). These two stations are located in the Eastern Lena Valley, with high rates of transport and sedimentation of the riverine suspended and resuspended particulate matter in the Laptev Sea (Wegner et al., 2005). Furthermore, the high content of total organic carbon at station 5221 also indicates the heightened sedimentation rate, as compared to the deeper stations to the north. The maximum bottom-water nutrient concentrations (ammonium, nitrogen, total and mineral phosphorus) and the minimum bottom-water oxygen content was observed in the bottom water around station 5221 (Stepanova et al., 2017), most likely related to intensive decomposition of organic matter. Unconsolidated sediments that are easily eroded and high sedimentation rates are obviously unfavorable for sedentary fauna that can be buried by redeposited sediments, and for tube-dwelling organisms, as the tubes may be buried, thereby impeding irrigation and leading to suffocation (Wlodarska-Kowalczuk et al., 2012). Deep-burrowing species are less likely to be affected by a disturbance at the sediment–water interface (Bolam et al., 2016). Indeed, the tube-dwelling worms (combination of traits: M2+FH1+LH1), such as Spiochaetopterus typicus, Maldane sarsi, M. arctica and Myriohele heeri, are almost absent at this area. Instead, the motile, burrowing sub-surface deposit feeders Scalibregma inflatum, Capitella capitata, Aricidea nolani (M1+FD2) prevail here. This conclusion is particularly corroborated by the relatively high abundance of C. capitata, an indicator species of organic enrichment and oxygen depletion.

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Thus, the first FCA axis describes the main part (over 50%) of functional variability of benthic assemblages and reflects the large-scale trend along the whole 500-km transect. The other part (displayed by the second FCA axe) reveals the smaller-scale response caused by local processes. The results of BTA cast light upon the probable mechanisms of changes in species composition, and the two analyses we perform enhance each other.

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4.3. Concurrence in taxa and traits composition and functional redundancy. Both structural and functional diversity indices showed strongly inter-correlated changes along the transect. Furthermore, arrangement of stations according environmental conditions, taxonomic composition and functional structure of assemblages yielded rather similar results. The matching is statistically supported by highly significant Mantel correlations between the respective resemblance/distance matrices. Noteworthy, all three biological estimators (species structure, phylogenetic composition and functional structure) mainly correlate with the first environmental component (Table 4), which incorporates multiple abiotic factors (Fig. 2). This congruence between these two dimensions of community organization suggests that the same complex of environmental factors (primarily riverine input and regime of sedimentation) has similar effect on both community structure and functioning. Such strong linkage between taxonomic and functional dimensions, both in terms of assemblages’ diversity and composition, is not the common case for marine macrofauna. For instance, ordinations based on taxa and function produced very different arrangement of stations along a Polar Front transect in the Barents Sea (Cochrane et al., 2012). Similarly, Frid and Caswell (2015) found a weak congruence in long-term changes of species and functional structure of the North Sea benthos. In both these studies, however, the authors dealt with much more species rich assemblages. Cochrane et al. (2012), for example, reported at average 99.7 which is twice more than in our data; assemblages studied by Frid and Caswell (2015) also exhibited 75-100 species per station. So rich species pools likely result in high functional redundancy, which ensures relative independence of community functions on species turnover in space and/or time (see below). By contrast, Micheli and Halpern (2005) found strong positive

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15 relatively species poor, low-redundant kelp forest

Our data also demonstrate strong linear relationship between species and functional diversity with slope value as high as 0.78 (Fig. 3i), indicating low functional redundancy of macrofaunal communities, i.e. weak or missing functional compensation by multiple species with shared traits. The lowest values of diversity and functional redundancy were observed on the stations close to the Lena Delta. At this habitat, fewer species occupied the available functional niche space and were likely to have fewer traits in common. Van der Linden et al. (2012) revealed similar pattern for the Mondego estuary (the NW coast of Portugal), with lower functional redundancy of macrofauna in the upper, desalinated part of the estuary with highly variable conditions.

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Few studies conducted in the eastern Laptev Sea allow us to compare our data on macrobenthic distribution to that described earlier for this region. The role of hydrological regime in benthic distribution has been described by Petryashov and Novozhilov (2004), who found a strong influence of salinity on species distribution, especially the dominance of bivalves Portalandia spp. in areas affected by the Lena riverine input and the increased role of echinoderms in deeper zone with normal salinity. Steffens et al. (2006) described the pronounced depth zonation in macrobenthic communities associated with the vicinity of Lena delta as well as the ice-cover regime. In particular, they distinguished a ‘‘Shallow’’ zone (<20 m), dominated by the crustaceans and molluscs, an ‘‘Intermediate’’ zone (20–30 m), characterised by a clear dominance of Portlandia arctica, and a ‘‘Deep’’ zone (>30 m) with bivalves and brittle stars being most abundant. Despite of obvious underestimation of polychaetes and overestimation of large crustaceans in their dredged samples, this zonation generally matches up our data. More detailed description of benthic communities and key species was presented by Gukov (1996, 2002, 2011). His generalized scheme of benthic zonation and dominating species turnover also corresponds well to our data. Unfortunately, neither full species lists nor coordinates of stations had been presented, so quantitative comparison is impossible.

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Thus, the overall spatial pattern of macrobenthic distribution corresponds well to that described for this region in preceding decades, indicating the long-term stability of the bottom ecosystem. On the other hand, low functional redundancy revealed in our study makes the ecosystem less buffered and thus more susceptible to a species loss or structural shifts caused by climatic changes or human activity. Biological trait analysis highlighted the typical traits for particular environments and has potential for a broader comparisons or revealing ecosystem shifts caused by local disturbances. However, more data from various Arctic regions are necessary before any general conclusions could be drawn.

We thank A.A. Udalov and M.I. Simakov for their help during the fieldwork, A.Yu. Miroshnikov for providing granulometric data, S.A. Shchuka and A.A. Polukhin for providing hydrological and hydrochemical data, and Dieter Piepenburg and anonymous reviewer for valuable comments to the draft version of manuscript. This study was supported by the Russian Scientific Foundation (grant № 14-50-00029, data analysis); and the Russian Foundation for Basic Research (grants № 14-50-00095, field research, and № 15-29-02507, biological traits database design).

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ACCEPTED MANUSCRIPT 19 Highlights:

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We studied distribution of macrobenthos on 500-km transect in the eastern Laptev Sea. Taxonomic and functional diversity and composition of macrofauna are strongly linked. Riverine input and sedimentation regime are the main factors affected both community structure and functioning. The benthic ecosystem exhibits long-term stability but low functional redundancy. This makes the ecosystem potentially susceptible to a species loss or structural shifts.

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