Community structure of demersal assemblages in the southwestern Black Sea

Regional Studies in Marine Science 32 (2019) 100844

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Community structure of demersal assemblages in the southwestern Black Sea ∗

Taner Yildiz a , , Mustafa Zengin b , Uğur Uzer a , F. Saadet Karakulak a , İlkay Özcan Akpınar c a

Faculty of Aquatic Sciences, Istanbul University, Istanbul, Turkey Central Fisheries Research Institute, Trabzon, Turkey c Izmir Directorate of Provincial Food Agriculture and Livestock, Izmir, Turkey b

article

info

Article history: Received 15 January 2019 Received in revised form 17 September 2019 Accepted 17 September 2019 Available online 20 September 2019 Keywords: Demersal species Assemblage Community Whiting Red mullet Western Black Sea

a b s t r a c t Available knowledge on the assemblage patterns of demersal macro-faunal species in the Black Sea is scarce. For this reason, data series of demersal trawl surveys between 2011 and 2014 were collected to identify the demersal assemblages along the continental shelf in the southwestern Black Sea. Data were analysed from 146 demersal trawl hauls conducted in the spring and autumn periods for three bathymetric contours: 0–20 m, 20–50 m, and 50–100 m. The spatial and temporal structural patterns of demersal zonation were assessed using multivariate analyses. Out of a total of 78 taxa, 69 demersal species were identified. Fishes showed the highest diversity with 41 species followed by 16 mollusks, 11 crustaceans, 5 echinoderms, 1 tunicate, and 1 porifera. Multivariate analyses revealed significant differences in the assemblages according to depth, sub-region, season, and year. Statistically, depth was the most influential factor determining the ordination of the faunal zonation. This study concludes that Merlangius merlangus, Mullus barbatus, Mytilus galloprovincialis, and Liocarcinus depurator may be the indicator species that make the greatest contribution to the formation of the demersal macro-community. © 2019 Elsevier B.V. All rights reserved.

1. Introduction Because of the unique ecological features and limited knowledge on the biodiversity of marine communities in the Black Sea, this basin is considered as a priority research area. Additionally, the Black Sea basin greatly influences the economy of all Black Sea countries (Eremeev and Zuyev, 2007). However, marine living resources are diminishing in the Black Sea whilst marine biological diversity is facing various threats from overfishing as well as illegal, unreported or unregulated fishing, pollution — both vessel and land-based, alien species, marine litter, and climate change (Öztürk et al., 2013). Furthermore, these anthropogenic activities in the Black Sea have shifted the ecosystem drastically to the level that some species have disappeared (Caddy, 1993; Prodanov et al., 1997). The Black Sea has been a traditionally important fishing area for industrial and artisanal fisheries. Major demersal resources in the Black Sea have been mainly dominated by several fish species such as whiting (Merlangius merlangus), red mullet (Mullus barbatus), and turbot (Scophthalmus maximus) (Knudsen et al., 2010). Currently, total annual landings of those species in the Turkish part of this basin have been recorded at over 5100 t (TUİK, 2017), ∗ Corresponding author. E-mail address: [email protected] (T. Yildiz). https://doi.org/10.1016/j.rsma.2019.100844 2352-4855/© 2019 Elsevier B.V. All rights reserved.

but many fisheries have gradually decreased. Unfortunately, 85% of the stocks are overexploited in the Black Sea (Daskalov, 2002; Sherman and Adams, 2010) thus compromising the economic welfare of the fishing industry. Moreover, few aquatic stocks in the Black Sea have been regularly assessed with short time-series for stock assessments by Scientific, Technical and Economic Committee for Fisheries of European Union (Raykov and Duzgunes, 2017). In recent decades, an increasing amount of experimental trawl surveys on demersal assemblages have been conducted in different areas of the Mediterranean Sea to understand the faunal zonation patterns. Using this approach, changes in community structure over depth on both the continental shelf and slope have been well-defined for many faunal communities (e.g. Stefanescu et al., 1992; Bertrand et al., 2002; Moranta et al., 1998; Politou et al., 2003). However, international survey programmes such as MEDITS (International bottom trawl survey in the Mediterranean) have not been conducted in the Black Sea due to lack of regional collaborations. Considering demersal studies in the Black Sea, surveys cover a period of over 45 years and have been mainly focused on number of species obtained, proportions of main taxa (%) and species within the total catch, and basic parameters of fish stocks assessment (e.g. Kutaygil and Bilecik, 1973, 1976; Bingel et al., 1996; Genç et al., 2002; Panayotova and Raykov, 2011). However,

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assemblage patterns of demersal species in the Black Sea have not been studied sufficiently using a multivariate approach. Faunal composition has important implications for the functioning of ecosystems. Understanding the causes of underlying diversity patterns, as well as their interaction with environmental factors, is important for ecosystem conservation purposes (Peristeraki et al., 2017). In this respect, the main objective of the study is to better understand macro-faunal species distribution and to define demersal community structure in the Western Black Sea using a fishery-independent data collection framework. 2. Material and methods 2.1. Study area and sampling design The surveys were conducted in the Western Black Sea from İğneada (Bulgarian border) to Karadeniz Ereğli between 2011 and 2014 (Fig. 1). The most appropriate sampling time during spring was between April 15th and May 15th: the period in which the spawning stock/mature individuals migrate to the coastal waters. By taking into account the migration and bio-ecological characteristics of the commercially important species (M. merlangus, M. barbatus, and S. maximus), the recruitment period between the end of September and October was suitable during fall. The study area was divided into three geographic sub-regions (K1, K3, and K5) in terms of geographical characteristics, the influence of river discharge, and fishing activity intensity. Additionally, the borders of these sub-regions were determined according to the stratified fisheries statistical data collection system established by the Ministry of Agriculture and Forestry, Republic of Turkey (Anon, 2016). The K1 sub-region is located inside the Pre-Bosphoric subecoregion and is under the influence of the Mediterranean–Black Sea interaction due to the presence of the Istanbul Strait (Öztürk et al., 2017). The Istanbul Strait acts as a biological barrier limiting the distribution of certain species of both Mediterranean and Black Sea origin (Öztürk and Öztürk, 1996). The main currents in the Black Sea are of a circular character and an anticlockwise direction (cyclonic currents). There are currents of low intensity in the waters, but the circulations are of an anticyclonic character (clockwise) in the coastal zones (Zaitsev, 2008). The Bosphorus eddy (in K1) and Sakarya eddy (in K5) are anticyclonic currents and influence the randomized distribution of eggs and population mixing. In addition, the Sakarya River discharges into the Black Sea in the town of Karasu, which changes the salinity in K5 (Yildiz et al., 2015). Fishing pressure mainly by bottom trawlers is higher in locations K1 and K3 (Yıldız and Karakulak, 2018). The depths surveyed were limited to maximum 100 m depth contour because its water composition of the Black Sea anoxic and contains high level of H2 S in layer between 100 and 200 m (Zaitsev and Mamaev, 1997). The sampling effort was not equally distributed over seasons, years, and regions due to constraints and conditions based on logistics and weather. For example, in 2012, surveys could not be performed due to maintenance of the research vessel. In the given fixed 39 stations, (Fig. 1), samplings runs of 30 min duration were conducted by towing the bottom trawl net at a speed of 2.5–3 knots depending on sea conditions and vessel. The stations were selected randomly, deploying a stratified sampling plan related to the depth ranges with the following bathymetric limits: 0–20 m, 20–50 m, and 50–100 m. The ecological requirements of the most important and dominant demersal fishes such as M. merlangus, M. barbatus, and S. maximus differ. M. merlangus is a cold-water fish, while M. barbatus is mostly distributed in the subtropical region, and S. maximus lives between the temperatures that these two fishes require. During the winter months, when the surface water temperature is at its lowest, stocks of

these three species are found at depths of 50–100 m. Due to stratification in the summer, they are found at different depths during reproduction periods (Genç et al., 2002). M. merlangus migrates to shallow water at 15–30 m in spring, and to deep waters at 80–100 m for spawning in autumn (Aksu, 2012). M. barbatus heads for shallow waters (0–20 m) for spawning in May, for medium depth layers (20–50 m) in August at the end of the spawning season, and for deeper waters from October–November (Genç, 2000). For the above mentioned reasons, the depth limits have been adopted to best cover the distribution areas of the main exploited or potentially exploitable species. The same sampling protocol was applied throughout this study on five research cruises of the RV Yunus S (31.8 m; 202 GT; 510 HP). A total of 148 hauls were performed during daylight hours, between sunrise and sunset. The same bottom trawl net with a 20 m headline and 16 mm of stretched full mesh size in the cod-end was deployed to maintain constant selectivity during the study due to the scope of Estimation of Demersal Fish Biomass in the Western Black Sea Project (BKDSTOK). The entire catch of each haul was sorted on board and all species were identified and counted. When the yield was small, the total weights and numbers were recorded directly; otherwise, a subsample was taken and sorted by the observers into the lowest possible taxonomic level. Fish species were identified using FishBase as reference (Froese and Pauly, 2018). Pelagic species (Engraulis encrasicolus, Pomatomus saltatrix, Trachurus sp., Sardina sp.) were excluded from the analyses since they were not been quantitatively sampled. 2.2. Data processing The catch of each haul was standardized (the number and weight of each species were converted into number and kilogrammes per km2 ) according to the ‘‘swept area’’ method (Sparre and Venema, 1992). The swept area was calculated by multiplying the tow distance by the net opening width. Statistical multivariate analyses were performed using resemblance-based permutation methods to assess communitybased assemblages on spatial and temporal differences covering depth, region, seasons, and years. The abundance data from the catch were transformed [log(x + 1)] and then rank-ordered using the Bray Curtis similarity matrix (Clifford and Stephenson, 1975). The grouping average strategy used was a hierarchical clustering algorithm to identify homogeneous groups (Sneath and Sokal, 1973). Nonmetric multi-dimensional scaling (MDS) was used to represent the samples as points in low-dimensional space, such that the distances apart of all points were as closely matched as possible to the relative dissimilarities (or distances) among the samples (Clarke and Gorley, 2015). One way analysis of similarities (ANOSIM) between hauls was used to determine whether the fish assemblage differed significantly (Clarke and Warwick, 2001). The species responsible for similarity/dissimilarity amongst factors were determined by the similarity percentages analysis (SIMPER) (Clarke and Warwick, 2001). Principal Coordinate analysis (PCO, i.e. metric multi-dimensional scaling) based on Bray–Curtis similarities matrix was used to explain the percentage of total variation in assemblage structure (Gower, 2005). All of the above-mentioned analyses were conducted using the PRIMER 6.0 computer package. 3. Results 3.1. Species composition A total of 78 species were found, with 68 of those being demersal species (according to FishBase), which included 44 species

T. Yildiz, M. Zengin, U. Uzer et al. / Regional Studies in Marine Science 32 (2019) 100844

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Fig. 1. The study area (K1-K3-K5 refers the sub-regions) and sampling stations located in the south-western coats of Black Sea, 2011–2014.

of fishes, 16 mollusks, 11 crustaceans, 5 echinoderms, 1 tunicate, and 1 porifera. The most significant group in the catches were represented by Osteichthyes, which accounted for 41 species, of which 32 were demersal. A large portion of the calculated demersal biomass, represented by 76.1% of the total, was composed of only two species, namely M. merlangus, and Mytilus galloprovincialis. Fish species were also dominated by M. merlangus, representing 74.3% of demersal fish biomass. Only three species of chondrichthyans were recorded, one shark (Squalus acanthias) and two rays (Raja clavata and Dasyatis pastinaca). Almost all of the species sampled were typical marine species with the exception of Acipenser gueldenstaedtii, Alosa immaculata, Atherina boyeri, and Liza aurata which are known to migrate to the inland waters. 3.2. Assemblage structure The nMDS plot (Fig. 2) and cluster dendrogram (Fig. 3) indicated a clear separation between the 0–20 m (A) and the 50–100 m stations (C). In the case of the 20–50 m group (B), the assemblage structure overlapped and was distributed across the other groups. However, Group A had a firmer orientation than the others by having higher average similarity of 56.4%. The distribution of M. merlangus and M. galloprovincialis (Fig. 4) were skewed to the right side of the plot, indicating a tendency to Group C. On the contrary, the distribution of M. barbatus and L. depurator were clearly skewed to the left side that is towards group A (Fig. 4). The PCO plot also showed distinct groups of samples and explained 57.1% of the total variance by abundance (Fig. 5). Table 1 shows the species that most contributed to differences between Group A and C according to SIMPER. The results of SIMPER and ANOSIM analyses agreed with the ordination of stations in relation to depth strata in the correspondence analysis. SIMPER results indicated an intermediate level of similarity between samples corresponding to each depth group. Between-group dissimilarities were higher than 59% in all cases, with the highest dissimilarities (86.6%) revealed by biomass between depth Groups A and C. Several species were recorded from more than one of the depth groups. Ninety percent of the total dissimilarity between depth communities by abundance was attributed to 33 species, and seven of these were high ranking contributors. However, a relatively small number of consolidating species mostly contributed to the average similarity of each depth group. Group C had the lowest number of species contributing to assemblage

composition itself. The number of discriminating species (contributing 90% of the dissimilarity) between depth groups ranged from 23 to 25 species by biomass and from 29 to 33 by abundance (Table 2). The ANOSIM test also indicated significant differences between years, regions and seasons (Table 3). However, the ordination of the data showed no clear separation or grouping in nMDS plots and dendrograms with year, region and season, being the factor of association. Apart from a spatial structure, the studied regions appeared to be homogeneous. From the seasonal perspective, the plots suggest that the spread of points overlapped. According to the SIMPER results, the differences among the two seasons were mainly characterized by five species: M. merlangus, M. galloprovincialis, M. barbatus, L. depurator, and Trachinus draco (Table 4). 4. Discussion The zonation pattern of demersal communities in the study area examined here indicates that the spatial structuring of the species assemblages were found to be influenced by depth, season, and annual changes in species abundance and biomass. As far as we know, this is the first such study on demersal assemblages across depths that has been conducted in the continental shelf in the Black Sea by utilizing multivariate assemblage-level tests. Obviously, depth is more influential than other factors judging by the higher R values in determining the demersal community assemblage found in the study area. As well-known, living organisms have specific levels of tolerance to various environmental variables, of which some are more important than others (Warwick and Uncles, 1980). Therefore, fish stocks are not randomly distributed over space (Law, 2000), and neither are other taxa. The interactions between the factors tested here were complex and, as a consequence, it could be elaborated that no factor could be assessed unilaterally. The Black Sea is the largest Sub-Area of the GFCM (SubArea 29) and one of the most complex ecosystems in the region (GFCM, 2012). However, life in the Black Sea has been restricted to a zone between the surface and 80–150 metres depth due to the existence of poisonous hydrogen sulphide gas at greater depths (Cihangir and Tıraşın, 1989). Despite the relatively narrow continental shelf (Zaitsev, 2008), data from this study suggests that the demersal community of the western Black Sea is dynamic and variable both spatially and temporally. The number of species obtained from bottom trawl nets in the Black Sea have been reported to be between 18 and 65; 26 species by

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T. Yildiz, M. Zengin, U. Uzer et al. / Regional Studies in Marine Science 32 (2019) 100844 Table 1 Results of SIMPER analysis showing fish species contributing to the dissimilarity between 0–20 m (A) and 50–100 m (C) depth groups in the western Black Sea area, 2011–2014. Groups A & C Average dissimilarity = 86.63

Group A

Group C

Species

Av.Abund

Av.Abund

Av.Diss

Diss/SD

Contrib%

Cum.%

Merlangius merlangus Mullus barbatus Liocarcinus depurator Mytilus galloprovincialis Trachinus draco Scophthalmus maximus Pegusa nasuta Rapana venosa Uranoscopus scaber Gobius niger Arnoglossus kessleri Neogobius melanostomus Raja clavata Platichthys flesus Squalus acanthias Stereoderma kirschbergi Chelidonichthys lucerna Liocarcinus navigator Dasyatis pastinaca Chamelea gallina Corella eumyota Eriphia verrucosa Scorpaena porcus

0.84 4.89 4.66 0.57 2.64 2.37 2.28 2.04 1.59 1.14 1.26 0.78 0.53 0.68 0.00 0.07 0.57 0.43 0.25 0.39 0.02 0.37 0.40

7.24 0.48 0.49 4.18 0.37 1.10 0.04 0.13 0.33 0.77 0.00 0.78 0.54 0.15 0.63 0.64 0.03 0.18 0.30 0.19 0.48 0.00 0.12

14.35 9.11 9.01 7.60 4.94 4.49 3.99 3.34 2.99 2.41 2.11 2.11 1.54 1.47 1.35 1.12 1.02 0.98 0.97 0.94 0.83 0.76 0.71

1.83 2.00 1.79 1.34 1.36 1.19 1.34 1.05 1.19 0.95 1.02 0.83 0.55 0.80 0.34 0.38 0.56 0.35 0.35 0.59 0.46 0.46 0.60

16.57 10.51 10.40 8.78 5.70 5.19 4.61 3.85 3.45 2.78 2.44 2.43 1.78 1.70 1.55 1.29 1.18 1.13 1.12 1.09 0.96 0.88 0.82

16.57 27.08 37.49 46.26 51.97 57.15 61.76 65.61 69.06 71.84 74.28 76.71 78.49 80.19 81.74 83.03 84.22 85.35 86.47 87.56 88.52 89.40 90.22

Fig. 2. Non-metric multidimensional scaling (NMDS) samples ordination for the three sampling depths (coastal and shelf depth samples: A: 0–20 m, B: 20–50 m and C: 50–100 m). Loge (x+1) transformed abundance of the western Black Sea area, 2011–2014.

Panayotova and Raykov (2011), 18 species by Aksu (2012), 26 species by Ceylan et al. (2014), 65 species by Akpınar (2015), 35 species by Panayotova and Todorova (2015), 32 species by Yıldız and Karakulak (2018). The highest number of species obtained was the 78 species from this study in the Western Black Sea. Indeed, it is already expected that the western portion is more diverse than the eastern part of the Black Sea due to the influx of Mediterranean originated waters. Amongst consolidating and discriminating species, M. merlangus, M. barbatus, M. galloprovincialis, and L. depurator seem to be key components of the demersal assemblages if we consider percentage contribution and they might be identified as ‘‘indicator" species of the demersal communities formed in different depths, seasons, regions, and years. The bathymetric distribution of M. merlangus, the moderately cold water species, in the study area is similar to that found in the other parts of Black Sea where it is mainly concentrated at depths

exceeding 50 m. It is the most abundant species amongst the observed species in almost all studies, referenced below. For this reason, Bradova and Prodanov (2003) indicated that M. merlangus was the key component of the Black Sea ecosystem. Işmen (2002) specified that its biomass was concentrated at depths over 50 m. Çiloğlu et al. (2002) reported that in the Eastern Black Sea, M. merlangus biomass at 35 m was proportionally less than at 60 m and 80 m and the maximum value in the total catch is at 80 m. Gönener and Bilgin (2006) revealed that in the Central Black Sea, M. merlangus accounted for 65.8% and 82.5% of total the total catch for greater and less than 75 m, respectively. Aksu (2012) noticed that in the Central Black Sea, depth was an important parameter for M. merlangus and that catches are always higher in fishing areas deeper than 50 m. According to Zaitsev and Mamaev (1997), M. galloprovincialis is widespread at depths of up to 40–50 m on the Black Sea shelf. Moreover, the largest aggregations are also reported at depths of

T. Yildiz, M. Zengin, U. Uzer et al. / Regional Studies in Marine Science 32 (2019) 100844

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Fig. 3. Hierarchical clustering assemblage of samples for the three sampling depths (coastal and shelf depth samples: A: 0–20 m, B: 20–50 m and C: 50–100 m). Loge (x+1) transformed abundance of the western Black Sea area, 2011–2014.

Fig. 4. The same nMDS of Fig. 2 with circles representing the log-transformed abundance of M. merlangius, M. galloprovincialis, M. barbatus, and L. depurator from the western Black Sea area, 2011–2014.

up to 20 m (Zaitsev and Mamaev, 1997). In the Ukrainian part of the Black Sea, it is distributed across wide areas at depths from the spray zone to 55 m (Zaitsev and Alexandrov, 1998). In contrast, in this study, M. galloprovincialis had the highest biomass in the 50–100 m group and its biomass at 20–50 m was very close to that of the 50–100 m group. Additionally, particularly on the Crimean Shelf, R. venosa is frequently encountered in the M. galloprovincialis biocoenosis (Zaitsev and Alexandrov, 1998). In fact, M. galloprovincialis is the main prey of R. venosa in the Black Sea (Seyhan et al., 2003). However, according to Chuhchin (1961) the habitats of M. galloprovincialis and R. venosa are not fully coinciding in the Black Sea. As an alternate factor, R. venosa might have be the driver of M. galloprovincialis biomass decline at 0–20 m in the study area. It is surprising that the densest R. venosa biomass was obtained at 0–20 m. This non-overlapping case in the study area could be possibly linked to the absence

of predators and food competitors of R. venosa. Changes in the biomass of both species can also be used as an important indicator for the high degree of destruction mainly caused by trawling in the benthic-benthopelagic habitat. It has been observed that the stocks of both species, which are selected as indicators in terms of fishing pressure, have been significantly exploited in the last decade (Beken et al., 2014). R. venosa population has spread gradually since 1970’s and its stock also started increasing in coastal benthic habitats in 1980s (STECF, 2015). R. venosa has established and put pressure on the bivalve communities through predation in the shallow waters of the Black Sea coast of Turkey (Bilecik, 1990). R. venosa gained commercial importance after 1985. Catches exceeded 10 thousand tons in 1989 and decreased to 2 thousand tons between 1995 and 2000. However, in recent years it is around 8 thousand tons. It has been reported that in the Eastern Black Sea, the densest biomass of M. barbatus is between 20–50 m and proportionally

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Fig. 5. Principal Coordinate Analysis (PCO) showing the dissimilarity relationships (left side by abundance; right side by biomass) based on the demersal assemblage structure which was classified according to the three depth groups (A: 0–20 m, B: 20–50 m and C: 50–100 m) in the western Black Sea area, 2011–2014. Table 2 The results of similarity percentage analysis (SIMPER-indicating percentage of similarity and dissimilarity with discriminating species low contributing to cut off 90.00%) by abundance and biomass, between the demersal assemblages from the given depths, regions, years and seasons in the western Black Sea area, 2011–2014. (AvSim: Average similarity; AvDis: Average dissimilarity; N: Number of species contributing). Abundance

Biomass

Depth

AvSim

Abundance N

AvSim

Biomass N

Pairwise

AvDis

N

AvDis

N

0–20 20–50 50–100

56.40 41.84 44.30

11 15 5

49.95 35.32 46.70

8 13 3

0–20; 20–50 0–20; 50–100 20–50; 50–100

59.76 83.78 71.24

31 29 33

66.43 86.63 71.84

25 23 25

34.55 34.87 38.47

11 15 15

30.66 31.61 36.27

9 13 11

1; 2 1; 3 2; 3

66.34 66.03 65.67

34 33 35

69.43 69.01 68.67

26 25 27

40.70 37.22 35.60

20 9 11

36.63 31.89 33.40

15 8 8

2011; 2013 2011; 2014 2013; 2014

68.21 68.50 64.85

33 33 25

73.66 71.20 68.16

27 27 18

35.53 36.26

14 14

34.63 31.64

10 11

Au; Sp

67.02

34

70.70

25

Region 1 2 3 Year 2011 2013 2014 Season Autumn Spring

Table 3 R-statistic values of ANOSIM and their significance levels for pairwise comparisons of demersal assemblage structure among depths, regions, years, and seasons in the western Black Sea area, 2011–2014 (ns: non-significant). Abundance

Biomass

Depth

Global R: 0.546

P-level

Global R: 0.519

P-level

0–20; 20–50 0–20; 50–100 20–50; 50–100

0.272 0.880 0.476

0.001* 0.001* 0.001*

0.249 0.882 0.384

0.001* 0.001* 0.001*

Region

Global R: 0.041

P-level

Global R: 0.025

P-level

1; 2 1; 3 2; 3

0.026 0.043 0.079

0.158ns 0.046** 0.005*

0.004 0.023 0.088

0.405ns 0.164ns 0.005*

Year

Global R: 0.168

P-level

Global R: 0.158

P-level

2011; 2013 2011; 2014 2013; 2014

0.283 0.190 0.019

0.001* 0.001* 0.271ns

0.310 0.166 0.034

0.001* 0.001* 0.215ns

Global R: 0.084

0.001*

Global R: 0.108

0.001*

Season Autumn; Spring *P < 0.01. **P < 0.05.

almost all of it is between 0–50 m (Genç, 2000). M. barbatus was

in the Central Black Sea (Turkey). In the same study, it was

caught for 12 months on the shores of Trabzon (eastern Black

noted that the amount of M. barbatus increases when approaching

Sea, Turkey) and intensively caught at 20–40 m (Genç, 2000).

shallow waters, and the opposite is true for M. merlangus. In

Aksu (2012) reported that it is fished at 0–40 m most intensively

the Samsun shelf area (Central Black Sea, Turkey), it has been

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Table 4 Results of SIMPER analysis showing fish species contributing to the dissimilarity between springs (Sp) and autumns (Au) in the western Black Sea area, 2011–2014. Groups Sp & Au Average dissimilarity = 70.70

Group Sp

Group Au

Species

Av.Abund

Av.Abund

Av.Diss

Diss/SD

Contrib%

Cum.%

Merlangius merlangus Mytilus galloprovincialis Mullus barbatus Liocarcinus depurator Trachinus draco Scophthalmus maximus Rapana venosa Uranoscopus scaber Neogobius melanostomus Gobius niger Pegusa nasuta Raja clavata Mesogobius batrachocephalus Squalus acanthias Scorpaena porcus Platichthys flesus Arnoglossus kessleri Dasyatis pastinaca Gaidropsarus mediterraneus Corella eumyota Liocarcinus navigator Chamelea gallina Chelidonichthys lucerna Stereoderma kirschbergi Acanthocardia tuberculata

5.68 3.29 2.22 1.84 1.43 1.56 1.46 0.81 1.15 1.46 0.84 0.95 0.57 0.34 0.52 0.47 0.49 0.04 0.45 0.37 0.63 0.48 0.22 0.33 0.42

2.64 2.47 3.22 2.90 2.08 1.65 1.41 1.82 1.31 0.72 0.99 0.45 0.59 0.45 0.74 0.59 0.53 0.75 0.44 0.46 0.10 0.24 0.36 0.19 0.11

9.02 6.42 5.77 5.21 3.59 3.52 3.08 2.99 2.70 2.50 2.21 1.81 1.50 1.46 1.43 1.42 1.27 1.20 1.09 1.06 1.05 0.97 0.82 0.80 0.74

1.12 1.11 1.23 1.13 1.14 1.00 0.97 1.07 1.04 1.01 0.86 0.63 0.64 0.39 0.79 0.80 0.73 0.42 0.74 0.55 0.44 0.54 0.49 0.31 0.40

12.76 9.07 8.16 7.38 5.08 4.98 4.35 4.23 3.82 3.53 3.13 2.56 2.12 2.07 2.02 2.00 1.80 1.70 1.54 1.50 1.48 1.37 1.17 1.12 1.05

12.76 21.83 29.99 37.37 42.46 47.43 51.78 56.02 59.84 63.37 66.50 69.06 71.17 73.24 75.26 77.27 79.06 80.76 82.31 83.81 85.29 86.67 87.83 88.96 90.01

found that M. barbatus stock is localized at depths generally below 30–50 m (STECF, 2014). In the study by Ceylan et al. (2014), M. barbatus accounted for 69.1% of the total commercial catch of demersal trawlers in the depth range of 10–57 m. Yıldız and Karakulak (2018) reported for commercial demersal trawling from the Western Black Sea that it is the characteristic species for the depth contours between 20–50 m and the same for M. merlangus between 50–100 m. In this study, M. barbatus was the most consolidating species along with L. depurator in the 0–20 m depth contour. Some species (such as L. depurator) have become dominant since other species were depleted in the benthic ecosystem. L. depratur is the most dominant type of Western Black Sea/Thracian seabed in terms of epifauna. Especially in 0–20 m depths of vertebrate fauna, the dominance of L. depurator may be due to the deterioration of the trophic food chain. This is one of the most important indicators of ecosystem overfishing. L. depurator is particularly characteristic for 0–50 m. It is estimated that the food chain is related to the change/degradation because of high abundance of this species. Excessive prey pressure on top predator species such as S. maximus, stingrays, and sharks may lead to an increase in opportunistic species populations of the food pyramid (Szostek et al., 2016). The benthic nutrient food chain in the Black Sea littoral has been largely disrupted due to the largest predators (cartilaginous fish; Squalus acanthias, R. clavata and turbot; S. maximus) whereas the abundance of scavenging crustaceans (especially L. depurator) feeding on the discards has increased. In the Black Sea coastal benthic habitat, R. venosa is the predominant predatory species in the food web. In addition, the most commonly seen element of epifauna was identified as L. depurator with a predator–scavenger feeding strategy (Zengin et al., 2014a). The landed catch amounts of the large predator species from the Turkish part decreased by 73%, 20% and 10%, respectively, compared to 50 years ago (TUİK, 2017). In the region, the abundance and spawning stock biomass of these demersal species have decreased (STECF, 2015) possibly due to overfishing pressure and high discard rates. S. maximus is the most valuable target species in the Black Sea littoral along

Turkish coasts. Turkey’s economy has been transforming from semi-state controlled state to a free market economy since 1980. After this period of rapid expansion in national economy, the fishing fleet grew uncontrollably due to subsidies, no custom duties and low interest credits, causing over investment in the sector meaning dramatic decline in demersal species in trawl fisheries for S. maximus, M. merlangus and M. barbatus. After this period, landings data have shown that fishing effort has gradually increasing after 1980’s while stock density of S. maximus declined 3.4 times in the last 20 years (Zengin et al., 2007). When the time-series is taken into consideration, the mean total length of S. maximus caught by experimental trawl surveys was 41.9 cm in 1990, decreased to 36.5 cm in 1996 (Zengin, 2000), then 35 cm in 2000 (Genç et al., 2002), 33 cm in 2003 (Zengin et al., 2007), 34 cm in 2005, 36 cm in 2007, and 34.2 in 2008 (Knudsen et al., 2010). The results of KARTRIP (Monitoring Project of BottomTrawling in Black Sea) surveys, showed estimated mean lengths of 32.6, 30, 27.7, 41.3 cm and 20.6 cm for the population for 2009, 2010, 2011, 2012 and 2014, respectively (Zengin et al., 2014a, 2015). All these reductions in the mean lengths show that there was a significant decrease in the stock abundance of S. maximus by the end of 2000s. Since 2010, a significant increase has been observed in the dotted goby (Neogobius melanostomus) population in the macro fish fauna assemblage in the southern Black Sea littoral region. A similar development has been identified in the two projects carried out by SUMAE (Central Fisheries Research Institute) in SSA (Samsun Shelf Area) (Zengin et al., 2014a,b). This increase in the population of N. melanostomus which is an important opportunistic species and which easily adapts to all kinds of ecosystem conditions, is an important indicator for the change in macrofauna in the Southern Black Sea ecosystem. A similar development has also been identified in the Baltic Sea (Puntila et al., 2018). Although depth is known to be one of the main environmental factors in distribution (e.g. Fujita et al., 1995; Gordon et al., 1995), many species undergo ontogenetic shifts as part of their life histories (Snover, 2008). In the Black Sea, spawning of most

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T. Yildiz, M. Zengin, U. Uzer et al. / Regional Studies in Marine Science 32 (2019) 100844

demersal fish species takes place in summer, with the exception of M. merlangus. The most notable feature of the assemblage dynamics were the changes in the relative abundance of some species. Panayotova and Todorova (2015) indicated the dissimilarity between spring and autumn as being 71.8% in Bulgarian part of the Black Sea which conforms to the present study where 70.7% dissimilarity was obtained between spring and autumn seasons. Indeed, more detailed experimental studies covering all seasons are needed all around the Black Sea. Future monitoring of indicator species is vital. Currently, many fish species such as Trachinus draco, Uranoscopus scaber, Gobius niger, and Neogobius melanostomus which are abundant in this study area are not managed or listed as a managed species by national authorities, but they are ecologically important, serving as either important predators or prey for other species. However, demersal fish species are the key group of marine organisms dominating the marine ecosystem of the Western Black Sea. Local stock assessment studies are carried out at both universities and research institutes, even if they are not undertaken at a nationwide level. These conclusions provide an effective regional-scale understanding of the demersal faunal community and spatial distribution in the Western Black Sea. This understanding of the key factors that influence demersal distribution in the Western Black Sea can help inform the design of future monitoring programmes and management of demersal populations in the area. It is also believed that the assemblage patterns revealed in this study will provide a baseline for assessing historical changes and the implementation of ecosystem-based management in the Western Black Sea. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Acknowledgements This study was supported by two projects from the General Directorate of Agricultural Research and Policies, Turkey (Project No: TAGEM/HAYSÜD/2011/09/02/06) and Scientific Research Projects Coordination Unit of Istanbul University, Turkey (Project # 5381). The authors would like to thank to Alan Newson (Editing and Proofreading Department of Istanbul University) and Aylin Ulman (Mediterranean Conservation Society) for English revisions. References Akpınar, I.Ö., 2015. Comparison of Catch Composition of Demersal Trawl Fishery Performed in Open and Closed Fishing Areas in Southern Black Sea (Ph.D. thesis). Çukurova University, Institute of Science, p. 270. Aksu, H., 2012. Investigation of Catch Efficiency and Catch Composition of Bottom Trawl Fishing Depending on Several Depths and Meteorological Criteria in Sinop Region (Ph.D. thesis). Sinop University, p. 147. Anon, 2016. Regulation for commercial fisheries in seas and inland waters for 2016–2020 fishing period, numbered 4/1 (No: 2016/35). General Directorate of Fisheries and Aquaculture (BSGM), Republic of Turkey Ministry of Food Agriculture and Livestock, Ankara, Turkey (in Turkish). Beken, Ç.P., Olgun, A., Yüksek, A., 2014. DeKoS Project (Marine and Coastal Waters Quality Determination and Classification Project, No: ÇTÜE 5118703) supported by the Ministry of Environment and Urbanisation, and coordinated by TUBITAK MAM. Bertrand, J.A., Leonori, I., Dremière, P.Y., Cosimi, G., 2002. Depth trajectory and performance of a trawl used for an international bottom trawl survey in the mediterranean. Sci. Mar. 66, 169–182. Bilecik, N., 1990. Distribution of sea snail, rapana venosa (v). In: Turkey’s Black Sea Coast of the Black Sea and the Impact of Fishing. Publication by TOKB Fisheries Research Institute, Bodrum, (in Turkish).

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