Distribution of aerobic anoxygenic phototrophs in the Eastern Adriatic Sea

Marine Environmental Research xxx (2017) 1e8

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Distribution of aerobic anoxygenic phototrophs in the Eastern Adriatic Sea


   Danijela Santi c a, Stefanija Sestanovi c a, *, Ana Vrdoljak a, Mladen Soli c a,
Nin
cevi c Gladan d, Michal Koblí
zek b Grozdan Ku
spili c c, Zivana Laboratory of Marine Microbiology, Institute of Oceanography and Fisheries,
Setali
ste I. Me
strovica 63, Split, Croatia Laboratory of Anoxygenic Phototrophs, Institute of Microbiology CAS, 379 81 Trebon, Czech Republic c Laboratory of Chemical Oceanography and Sedimentology of the Sea, Institute of Oceanography and Fisheries,
Setali
ste I. Me
strovica 63, Split, Croatia d Laboratory of Plankton and Shellfish Toxicity, Institute of Oceanography and Fisheries,
Setali
ste I. Me
strovica 63, Split, Croatia a

b

a r t i c l e i n f o

a b s t r a c t

Article history: Received 25 April 2017 Received in revised form 17 July 2017 Accepted 18 July 2017 Available online xxx

The spatial patterns of aerobic anoxygenic phototrophs abundances were investigated, for the first time, in the Adriatic Sea. Also, the spatial patterns of the whole picoplankton community as well as the environmental factors that potentially influence these patterns were highlighted. AAP abundances was in average 66.9 ± 66.8
103 cell mL1, and their proportion in total bacteria was 7.3 ± 4.3%. These values are in the upper range of AAP abundances observed in marine environments. Multivariate analyses proved that environmental factors influenced the picoplankton community interdependently. Chl a was the main driving factor for the picoplankton community, accounting for 33.3% of picoplankton community variance, followed by NO 2 (17.9% of variance explained) and temperature (14.2% of variance explained). Chl a showed stronger correlation with AAPs, non-pigmented bacteria and Picoeucaryotes than with cyanobacteria. Abundance of cyanobacteria was stronger correlated to salinity and the N:P ratio than to nutrient concentrations. © 2017 Elsevier Ltd. All rights reserved.

Keywords: Aerobic anoxygenic phototrophs Adriatic sea Picoplankton

1. Introduction Marine picoplankton encompass the smallest (<2 mm) marine organisms such as cyanobacteria, picoeukaryotes and nonpigmented bacteria. Marine picocyanobacteria are major contributors of biomass and primary production thus giving them an important role in food web dynamics and the carbon cycle in marine ecosystems (Li, 1994; Partensky et al., 1996; Grob et al., 2007). About 40 years ago, a novel bacterial functional group with small amounts of bacteriochlorophyll (BChl) a was discovered in Tokyo Bay, Japan (Harashima et al., 1978; Shiba et al., 1979). This group of bacteria, the aerobic anoxygenic phototrophs (AAPs), was found to account for a significant fraction of the microbial communities in marine environments (Kolber et al., 2001; Cottrell et al., 2006; Ma
sín et al., 2006; Sieracki et al., 2006; Lami et al., 2007; Michelou et al., 2007; Zhang and Jiao, 2007; Salka et al., 2008;

* Corresponding author.

  E-mail addresses: [email protected] (D. Santi c), [email protected] (S. Sestanovi c), ana.
 [email protected] (A. Vrdoljak), [email protected] (M. Soli c), [email protected] (G. Ku
spili c),
Nin
[email protected] (Z. cevi c Gladan), [email protected] (M. Koblí
zek).

Cottrell et al., 2010; Boeuf et al., 2013). In contrast to most anoxygenic phototrophs, AAPs photosynthesize and grow only in the € bler, 2006; Yurkov and presence of oxygen (Biebl and Wagner-Do Csotonyi, 2009; Koblí
zek et al., 2010). Their primary metabolism is mostly heterotrophic (Harashima et al., 1987) but they can additionally satisfy their energy needs by utilizing the light harvesting pigment BChl a (Yurkov and van Gemerden, 1993; Fuchs et al., 2007; Hauruseu and Koblí
zek, 2012). AAP has been a major topic in aquatic microbiology in the last two decades. Recent studies report on their unique role in ocean carbon cycling (Kolber et al., 2001; Jiao et al., 2003; Koblí
zek et al., 2007). AAPs questioned the classical view that marine bacteria are solely heterotrophic organisms fully dependant on recycled dissolved organic matter produced by photoautotrophic phytoplankton. Their ability to obtain energy by harvesting light and consuming organic substrates has led to considering their potential competitive advantage over strict heterotrophs in aquatic ecosystems (Ferrera et al., 2017). A large number of ecological studies on AAPs have been carried out in open ocean waters, such as the Pacific (Cottrell et al., 2006; Lami et al., 2007; Ritchie and Johnson, 2012) and the Atlantic

http://dx.doi.org/10.1016/j.marenvres.2017.07.012 0141-1136/© 2017 Elsevier Ltd. All rights reserved.


c, D., et al., Distribution of aerobic anoxygenic phototrophs in the Eastern Adriatic Sea, Marine Please cite this article in press as: Santi Environmental Research (2017), http://dx.doi.org/10.1016/j.marenvres.2017.07.012

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2

(Sieracki et al., 2006; Koblí
zek et al., 2007; Michelou et al., 2007). AAPs have also been investigated in enclosed seas, such as the Black Sea (Koblí
zek et al., 2006), the Baltic Sea (Koblí
zek et al., 2005; Salka et al., 2008) and the Mediterranean Sea (Lami et al., 2009; Ferrera  et al., 2011; Lamy et al., 2011a, 2011b). et al., 2011; Hojerova The picoplankton community structure in the Adriatic Sea has been studied intensively over the past few decades (Vilibi c and


  Santi c, 2008; Soli c et al., 2008, 2009, 2010, 2015; Silovi c et al.,

 c et al., 2015). However, 2011; Santi c et al., 2011, 2012; Sestanovi the data on AAP presence and distribution patterns is scarce. So far, to our knowledge, only one study has explored the presence of AAP in the Adriatic Sea based on the concentration of BChl a (Celussi et al., 2015). Therefore, this survey is performed in order to determine AAPs abundances. We aimed to investigate the spatial patterns in their abundances in two different water types (coastal and transitional waters) along the eastern Adriatic coast. In addition, we highlighted the spatial patterns of the whole picoplankton community as well as the environmental factors that potentially influence these patterns. The results presented in this study constitute the first direct quantification of AAP abundances in the Adriatic Sea. 2. Materials and methods 2.1. Study area Sampling was performed along the eastern Adriatic coast (Fig. 1) on board the RV Bios 2 in August 2015.

The samples were collected at 24 stations. Six were chosen in transitional waters (stations B1, B2, C1, C2, D1 and E1) and 18 were in coastal waters. Transitional and coastal water definitions correspond to the Water Framework Directive 2000/60/EC definition of waters. Transitional waters represent estuaries or mouths of Croatian rivers Krka, Jadro, Neretva and Ombla. They are characterized by shallow depths, high phosphate and low salinity values due to the substantial influence of freshwater flows. The largest variations in basic hydrographic parameters are found in the sur
 face layer of a particular river (Soli c et al., 2015). Coastal waters are located further towards the open sea and have the typical biogeochemical features of marine waters. 2.2. Environmental parameters Water samples were collected from the surface at all stations using 5 L Niskin bottles. A Seabird 25 CTD profiler recorded temperature and salinity data. Dissolved oxygen was determined by Winkler titration (Strickland and Parsons, 1972). Dissolved inorganic nutrient concentrations (nitrates, nitrites, ammonia and soluble reactive phosphorus) were determined colorimetrically using the auto-analyser modified method by Grasshof (1976). Chlorophyll a (Chl a) was determined in 500 mL samples that were filtered through Whatman GF/F glass-fibre filters and stored at 20  C. These were homogenized and extracted in 90% acetone. Samples were analysed using a Turner TD-700 Laboratory Fluorometer calibrated with pure Chl a standards (Strickland and Parsons, 1972).

Fig. 1. Sampling stations in the Eastern Adriatic Sea.


c, D., et al., Distribution of aerobic anoxygenic phototrophs in the Eastern Adriatic Sea, Marine Please cite this article in press as: Santi Environmental Research (2017), http://dx.doi.org/10.1016/j.marenvres.2017.07.012

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2.3. Picoplankton abundance Two mL water samples were fixed with 2% formaldehyde. Abundances of Synechococcus (Synecho), Prochlorococcus (Prochl), picoeukaryotes (PicoEu) and SybrGreen I-stained non-pigmented bacteria (HB) were determined by flow cytometry (Marie et al., 1997) using an XL-MCL cytometer. Different populations of HB were distinguished according to light diffraction and emission. For microscopy analyses, 10e20 mL of the fixed samples were filtered through a 0.2 mm polycarbonate filter. Cells were stained with 40 ,6-diamidino-2-phenylindole (DAPI, 1 mg mL1, final concentration) and counted using a Zeiss Axio Imager Z2 microscope equipped with a Plan-Apochromat 63
objective lens and an HXP120C metal halide lamp. Several images per sample (with >100 cells in each) were taken using a Hamamatsu EM-CCD C9100 B/W camera. Three fluorescence images were taken from each frame: total DAPI-stained bacteria in the blue part of the spectrum; Chl a autofluorescence in the red part of the spectrum and, finally, both BChl a and Chl a containing cells were recorded in the infrared part of the spectrum (>850 nm) (Ma
sín et al., 2006). To distinguish between non-pigmented bacteria, picocyanobacteria and AAPs image acquisition and manipulation were done using the standard Zeiss AxioVision ver. 4.8 program. 2.4. Statistical analysis A Pearson correlation analysis was carried out to examine the relationship between picoplankton community members and environmental variables. The response of the picoplankton community to environmental conditions was analysed using multivariate statistical analyses. Redundancy analysis (RDA) was performed
using CANOCO 5 (Ter Braak and Smilauer, 2012) to evaluate the influence of different environmental factors on picoplankton community distribution. The ordination axes in the RDA are constrained by linear combinations of environmental variables; thus, RDA explicitly models response variables as a function of explanatory variables (Zuur et al., 2007). The significance of the ordination axes was tested with Monte Carlo permutation tests (Legendre and Legendre, 1998). Model results were reproduced in ordination biplots summarizing the main trends in the data. To investigate which subset of environmental variables relates best to a picoplankton community, a multivariate BIO-ENV procedure (Clarke and Warwick, 2001) was used. This analysis compares rank correlation between the matrix of environmental variables (based on normalised Euclidean distance) and the biotic similarity matrix of picoplankton variables (based on Bray-Curtis similarity) using different permutations of the environmental variables. The strength of the correlation is assessed based on nonparametric Spearman rank correlation (q), which ranks the subsets of variables that best ‘match’ the biological patterns. The highest coefficient at each level of complexity is tabulated and can be interpreted as the ‘best explanatory environmental variable’ of the community assemblage. 3. Results 3.1. Environmental conditions The sampling was performed at 24 stations representing various physical, chemical and biological characteristics (Table 1). Transitional water stations were characterized by low salinity values (range 9.59e35.34 psm) and high concentrations of majority of nutrients. Coastal stations displayed more uniform salinities, typical of marine waters (range 35.37e38.30 psm) and lower nutrient concentrations.

3

Surface Chl a concentration varied over a broad range (0.05e2.83 mg m3). Most of the stations were oligotrophic with Chl a values below 0.9 mg m3. The stations influenced by river Jadro (stations C3, C4 and C5) and the river Krka (B1 and B2), where Chl a values reached much higher levels (1.28e2.96 mg m3), constituted exceptions. 3.2. Abundances of non-pigmented bacteria and AAPs Abundance of non-pigmented bacteria varied greatly among stations, ranging between 0.20
106 and 1.56
106 cells mL1 (av ± sd 0.62 ± 0.42
106 cells mL1) (Fig. 2). Almost all the stations in coastal waters exhibited values lower than 1
106 cells mL1. The majority of stations in transitional waters showed values higher than 1
106 cells mL1 (e.g. stations that are under the direct influence of rivers Krka (B1, B2) and Jadro (C1, C2). AAP bacteria were observed in all samples. Their abundances varied significantly across the stations, from 10
103 to 240
103 cells mL1 with an average value of 70 ± 66.77
103 cells mL1. Similarly to Chl a distribution AAPs were most abundant at the stations in the vicinity of river Jadro (C2, C3, C4 and C7) and river Krka (B2), with values ranging from 130
103 to 240
103 cells mL1. The lowest AAP abundances were recorded at the estuaries of rivers Ombla (stations E1 and E2) and Neretva (station D1). AAPs represented between 2.49 and 19.59% of total bacteria (average value of 7.26 ± 4.31%), a similar fraction in both types of water (from 2.40 to 12.62% in coastal waters and from 3.77 to 19.59% in transient waters) (Fig. 2). At the majority of stations, % AAP was lower than 10%. The stations influenced by river Jadro (C2, C3 and C4) and coastal station A2, where AAPs comprised somewhat larger fractions of the total prokaryotic community than at other stations (on average 15.29 ± 3.56%), constituted exceptions. AAPs were always much more abundant than autotrophic picoplankton, except at station C5 where Prochl and Synecho exhibited a pronounced maximum (Fig. 3). The abundances of AAP cells dominated over cyanobacteria especially at the stations in transitional waters. In these waters AAP abundance was 2e29-fold higher than Synecho and 3e95-fold higher than Prochl abundances. In coastal waters, AAP bacteria were as much as 5-fold more abundant than Synecho and 14-fold more abundant than Prochl. 3.3. Abundances of autotrophic picoplankton Abundances of Synecho and Prochl ranged from 1.83
103 to 345
103 cells mL1 (av ± sd 32.28 ± 68.16
103 cells mL1) and from 0.64
103 to 371
103 cells mL1 (24.41 ± 72.82
103 cells mL1) respectively (Fig. 3). Synecho was always more abundant than Prochl. These organisms were about one order of magnitude more abundant at stations that are influenced by rivers Jadro (C2 and C3) and Neretva (D2) compared to the other stations. At station C5, abundances of both groups were 3 orders of magnitude higher than at other stations. This area in the vicinity of river Jadro has already been described as an area with higher trophic status compared to other regions (Marasovi c and Nin
cevi c, 1997). Compared to the variations in Prochl and Synecho abundances, abundances of PicoEu fluctuated in a rather narrow range (from 1.79
103 to 42.03
103 cell mL1 with an average value of 8.59 ± 8.93
103 cell mL1) (Fig. 3). Their abundances were consistently lower than those of Prochl and Synecho except at station A2 where we recorded the maximum value of 42.03
103 cell mL1. The stations in the vicinity of rivers Jadro (C2 and C3), Krka


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Table 1 Characteristics of waters sampled in the Central Adriatic Sea in August 2015: Temperature (T), salinity (S), dissolved oxygen (O2), chlorophyll a (Chl a) and nutrient concentrations in the surface layer; NO2-, nitrites, NO3-, nitrates NH4þ, ammonium; SRP, soluble reactive phosphorus. Stations

Bottom depth (m)

Coastal waters A1 44 A2

10

A3

46

A4

43

A5

29

A6

64

B3

20

C3

17

C4

19

C5

35

C6

41

C7

9

C8

50

D2

14

D3

35

D4

58

D5

76

E2

30

Transitional waters B1 15 B2

34

C1

1.5

C2

4

D1

22

E1

4

Geographic location

T ( C)

S

O2 (mL L1)

NO-3 (mmol L1)

1 NO 2 (mmol L )

NH4

SRP (mmol L1)

Chl a (mg L3)

15 24.420 E 44 16.950 N 15 2.900 E 44 26.820 N 15 0.720 E 44 29.240 N 14 51.780 E 44 17.660 N 15 12.500 E 44 6.600 N 15 13.720 E 43 57.000 N 15 51.710 E 43 39.000 N 16 27.200 E 43 31.800 N 16 24.110 E 43 32.500 N 16 22.900 E 43 31.100 N 16 12.500 E 43 30.200 N 16 26.030 E 43 30.190 N 16 23.900 E 43 25.600 N 17 39.000 E 42 53.010 N 17 19.710 E 43 2.010 N 16 53.710 E 43 2.010 N 17 33.700 E 42 47.510 N 18 11.700 E 42 36.510 N

24.54

35.71

4.89

2.55

0.61

1.47

0.08

0.47

26.40

37.20

5.35

0.17

0.10

2.83

0.03

1.10

24.79

37.54

5.51

0.33

0.09

1.28

0.03

0.43

23.78

38.12

5.35

0.55

0.05

0.55

0.03

0.14

24.31

37.41

4.96

0.13

0.10

0.34

0.03

0.33

24.66

38.21

5.00

0.20

0.05

0.07

0.03

0.22

25.47

38.28

4.94

0.32

0.12

0.57

0.03

0.10

26.84

36.46

5.01

0.02

0.66

1.03

0.10

1.87

26.32

35.71

5.12

0.67

0.09

0.46

0.08

2.24

26.27

36.62

6.77

0.64

0.16

0.57

0.03

1.28

26.24

37.49

4.81

0.31

0.02

0.66

0.03

0.30

25.15

37.16

4.91

0.59

0.05

0.37

0.03

0.66

26.56

37.21

4.73

0.57

0.01

0.97

0.03

0.17

25.24

35.37

5.11

0.42

0.16

0.94

0.09

0.87

25.00

33.73

4.68

0.13

0.12

0.61

0.03

0.27

25.83

38.02

4.81

0.10

0.12

0.22

0.03

0.07

26.60

37.75

4.73

0.27

0.06

0.07

0.03

0.15

24.52

36.41

5.09

3.02

0.17

1.45

0.03

0.32

15 52.160 E 43 48.760 N 15 51.530 E 43 45.350 N 16 28.990 E 43 31.990 N 16 28.270 E 43 32.050 N 17 26.890 E 43 0.310 N 18 7.990 E 42 40.250 N

27.03

22.77

5.96

0.62

0.00

0.64

0.09

2.36

26.19

28.59

5.66

3.23

0.21

0.84

0.15

2.96

27.07

35.06

6.39

36.17

0.55

3.98

0.67

0.82

27.80

35.10

5.92

30.44

0.65

1.87

0.19

0.78

25.52

36.34

5.00

0.31

0.11

0.56

0.03

0.49

17.34

9.59

6.37

41.78

0.00

1.83

0.48

0.17

(B1 and B2) and Neretva (D2) showed higher PicoEu abundances compared to other stations. 3.4. Distribution of bacterial assemblages in relation to environmental variables To explore the patterns in picoplankton abundances in relation to the environmental parameters, a Pearson's correlation analysis was used. This analysis showed that Chl a and NO 2 were the most important environmental factors for picoplankton community. Correlation coefficients between Chl a and AAP abundances (r ¼ 0.80; n ¼ 24; P > 0.05), Chl a and % AAP (r ¼ 0.59; n ¼ 24; P > 0.05), and between Chl a and HB abundances (r ¼ 0.91; n ¼ 24; P > 0.05) showed that both groups of bacteria responded to this environmental parameter in a similar way. The results also show that higher trophic environments harbour higher abundances of

þ

(mmol L1)

both groups (Fig. 4). Nitrites concentrations showed significant correlation with AAP abundances (r ¼ 0.57; n ¼ 24; P > 0.05), %AAP (r ¼ 0.59; n ¼ 24; P > 0.05) and HB abundances (r ¼ 0.54; n ¼ 24; P > 0.05). No significant correlations were found between cyanobacteria and any of the environmental parameter. To analyse the main physicochemical factors affecting picoplankton abundance, we performed RDA ordination of picoplankton groups with respect to environmental variables (Fig. 5). Table 2 presents the summary of the analysis. The Monte Carlo permutation test showed that environmental factors were significantly correlated with the first axis (F ¼ 16.1; P ¼ 0.003) and all other axes (F ¼ 3.3; P ¼ 0.002). The chosen set of explanatory variables accounted for 68% of total variance in picoplankton. The first two axes explained 60.6% of picoplankton variance. The first axis was mainly defined by Chl a, NO 2 and


c, D., et al., Distribution of aerobic anoxygenic phototrophs in the Eastern Adriatic Sea, Marine Please cite this article in press as: Santi Environmental Research (2017), http://dx.doi.org/10.1016/j.marenvres.2017.07.012

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Fig. 2. Abundances of non-pigmented bacteria (HB) and AAP bacteria in August 2015 in the Eastern Adriatic surface waters.

Fig. 3. Abundances of autotrophic picoplankton (Synecho- Synechococcus; Prochl- Prochlorococcus; PicoEu- Picoeukaryotes) in August 2015 in the Eastern Adriatic surface waters.

Fig. 4. Linear regression between chlorophyll a (Chl a) and non-pigmented bacteria abundances (HB) (dashed line), between Chl a and %AAP (grey solid line) and between Chl a and AAPs abundances (black solid line).

temperature (intraset correlation coefficients: 0.70, 0.51 and 0.46, respectively). Chl a was the main driving factor for the picoplankton community, accounting for 33.3% of picoplankton community variance (F ¼ 11.0; P ¼ 0.002) followed by NO 2 (17.9% of variance explained, F ¼ 4.8; P ¼ 0.01).

Picoplankton community members were grouped into two distinct segments, based on the correlation between them. AAPs, non-pigmented bacteria and PicoEu were closely related, which was also the case for Synecho and Prochl. Both types of cyanobacteria were loosely associated with AAPs, non-pigmented bacteria


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importance of NO 2 and O2, combined with Chl a, for the picoplankton community was similar. 4. Discussion

Fig. 5. Redundancy analysis (RDA) correlation diplot for picoplankton abundances and environmental factors (T, temperature; S salinity; O2, dissolved oxygen; NH4, ammonium; SRP, soluble reactive phosphorus; N/P; dissolved inorganic nitrogen: phosphate ratio; Chl a, chlorophyll a; AAP, aerobic anoxygenic bacteria; Synecho, Synechococcus; Prochl, Prochlorococcus; PicoEu, Picoeucaryotes; HB, non-pigmented bacteria). The biplot displays response and explanatory variables as vectors (arrows point in the direction of increasing variable values) in a reduced ordination space. The arrow indicates the direction of the steepest increase of the variable. Correlations between variables are shown by the angle between arrows (an angle <90 between two arrows of interest implies positive correlation), whereas the length of an arrow depicts the strength of association between a variable and the ordination axes shown in the biplot.

Table 2 Summary table presenting the results of the redundancy analysis (RDA) of the picoplankton groups and the environmental variables. Statistics

Axis 1

Axis 2

Axis 3

Axis 4

Eigenvalues Explained variation (cumulative) Pseudo-canonical correlation Explained fitted variation (cumulative)

0.5344 53.44 0.9024 78.54

0.0719 60.63 0.5989 89.11

0.0367 64.30 0.7899 94.51

0.0292 67.23 0.7689 98.81

and PicoEu. Chl a showed stronger correlation with AAPs, nonpigmented bacteria and PicoEu than with cyanobacterial cluster, as indicated by the perpendicular projection of the picoplankton member arrow-tips on the line overlaying the Chl a arrow. Cyanobacteria were more related to salinity and the N:P ratio rather than to nutrient concentrations. The BIO-ENV procedure was used to explore further, which combination of environmental variables related best to picoplankton community assemblages. Chl a explained most of the picoplankton community variability across the entire sample set, giving an overall rank coefficient of q ¼ 0.723. When NO 2 is introduced in the analysis, explanation of community variability decreases to q ¼ 0.631. When O2 is further introduced as the next most important variable, the value of the correlation coefficient is further slightly reduced to q ¼ 0.626. These results show that the

This study showed that AAPs were abundant in the Middle and the South Adriatic coastal waters (up to 2.56
105 cells mL1). These values are in the upper range of AAP abundances observed in marine environments, more comparable to the range reported for estuaries (Waidner and Kirchman, 2007; Cottrell et al., 2010) and lakes (Fauteux et al., 2015). The abundance of AAPs in the Mediterranean Sea has been recorded in several studies (Lami et al.,  et al., 2011; Lamy et al., 2009; Ferrera et al., 2011, 2014; Hojerova 2011a, 2011b). These studies revealed that AAP abundances in the Mediterranean Sea could reach up to 135
103 cells mL1 in the western part and only up to 0.9
103 cells mL1 in the eastern part. AAPs in the Adriatic Sea accounted for a relatively high proportion of total bacteria (from 2.49 to 19.89%). AAPs typically represent 1e10% of total prokaryotes in the oligotrophic oceans (Sieracki et al., 2006; Jiao et al., 2007; Yutin et al., 2007; Ritchie and Johnson, 2012) while in shelf seas or river estuaries they can represent 1e34% of total prokaryotes (Waidner and Kirchman, 2007). In Mediterranean waters, AAP bacteria represent 1%e11%  et al., 2011; Ferrera et al., 2011, 2014). of total prokaryotes (Hojerova Celussi et al. (2015) speculated, based on the concentrations of BChl a, that AAPs might represent up to 10% of total prokaryotes in the open waters of the Adriatic Sea. This assumption is consistent with our results since the average contribution of AAPs to total nonpigmented bacteria was around 7%. Higher AAP standing stocks and a higher share in total bacteria numbers were found in the vicinity of rivers, most prominently near Krka (B1, B2) and Jadro (C1, C2). These areas are subject to high anthropogenic pressures and have already been described as the most productive coastal areas along the eastern Adriatic (Marasovic et al., 2006). Krka estuary is characterized by a higher content of dissolved organic matter and detrital particles while the area in the vicinity of river Jadro is under the strong impact of untreated
 municipal and industrial effluents (Zuti c and Legovi c, 1987; Legovic et al., 1994; Cetinic et al., 2006). AAP bacteria seem to be more abundant in mesotrophic coastal and estuarine waters than in the open sea (Schwalbach and Fuhrman, 2005; Cottrell et al., 2006; Sieracki et al., 2006; Jiao et al., 2007; Lami et al., 2007; Cottrell et al., 2010). One of the reasons for higher abundances of AAPs in estuarine waters than in the open sea could be the association of AAPs with particles in these turbid environments, which can provide an optimal environment for their growth and protection against grazing. Data from Delaware and Chesapeake estuaries (Waidner and Kirchman, 2007) and the coastal western Mediterranean Sea (Lami et al., 2009) show that the majority of the AAP community in these environments were attached to particles. On the contrary, AAPs in the open sea are mostly free-living. The terrestrial inputs from karstic Adriatic rivers and underground springs bring large amount of water
enriched with particles and nutrients (UNEP/MAP, 2003; Canjevac and Ore
si c, 2015). This influx of freshwater determines the structural characteristics of the picoplankton community, leading to the
c et al., 2015). increase in picoplankton counts and production (Soli Although our data cannot confirm the effect of the particle association and AAPs we assume that this can be the reason for higher AAP numbers in coastal and estuarine waters as the pattern of higher percentages of attached bacteria in turbid environments is a feature common to all prokaryotic cells (Simon et al., 2002). Our results show that higher trophic environments harbour higher abundances of AAP as shown by their significant correlation with Chl a. This has already been well-documented for the Pacific,


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7

under Grant IP-2014-09-4143 “Marine microbial food web processes in global warming perspective” (MICROGLOB) and Grant IP2014-09-3606 “Marine plankton as a tool for assessment of climate and anthropogenic influence on the marine ecosystem” (MARIPLAN). The work of Michal Koblí
zek was supported by the MSMT project Algatech Plus (Grant number LO1416). Acknowledgments We thank Hrvatske vode for the permission to use the environmental data. References

Fig. 6. Abundances of aerobic anoxygenic bacteria in different marine environments (the Adriatic Sea data: from this study; the Mediterranean Sea data: from Hojerova et al., 2011; the Baltic Sea data: from Ma
sín et al., 2006).

Atlantic and Indian ocean (Jiao et al., 2007); however, the interpretation of the observed relationship is not straightforward. It might reflect the dependence of AAPs on dissolved organic matter from phytoplankton or the co-dependence of bacteria and primary producers on limiting nutrients such as phosphate or nitrate. AAPs mainly grow heterotrophically and use light as an additional source of energy when organic carbon is scarce (Kolber et al., 2001). Under organic-rich conditions, they switch to the mostly heterotrophic metabolism as photosynthesis apparently offers fewer advantages (Yurkov and Csotonyi, 2009). Sufficient pools of organic matter in the estuaries and coastal waters of the Adriatic probably offer them suitable environmental conditions for their heterotrophic growth. The abundance of non-pigmented bacteria also tends to increase in line with Chl a suggesting that both types of bacteria respond to the same environmental drivers and are subject to similar regulating factors. To compare our data with available data from the Mediterranean and the Baltic Sea AAP abundances were plotted against Chl a concentrations (Fig. 6). It can be seen that the general trend of higher AAP numbers in higher trophic environments also exist in these different marine provinces. Obviously, the trophic status of an area plays an important role in the distribution of AAPs. Numerous surveys show that environmental factors such as nutrient concentration or temperature have a profound impact on overall picoplankton community composition and diversity in the
c et al., 2009, 2010, 2015; Santi
 Adriatic Sea (Soli c et al., 2012). Our research showed that selected environmental factors also regulate the dynamics of AAPs in the Adriatic Sea during summer. The distribution of AAPs was mainly driven by changes in Chl a concentrations, and also by NO 2 and temperature. In contrast, none of the chemically different forms of phosphorus influenced the AAP abundances, despite the previous observations that suggested that summertime picoplankton community was strongly limited by
c phosphorus (UNEP/MAP, 2003; Nin
cevi c Gladan et al., 2006; Soli et al., 2015). This initial study of AAPs abundance and their distribution in the eastern Adriatic Sea has confirmed AAP bacteria to be significant part of the total bacterial abundance. Further studies should include the investigations of temporal distribution of AAP and potential environmental factors controlling this dynamics. Funding This research was supported by the Croatian Science Foundation

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c, D., et al., Distribution of aerobic anoxygenic phototrophs in the Eastern Adriatic Sea, Marine Please cite this article in press as: Santi Environmental Research (2017), http://dx.doi.org/10.1016/j.marenvres.2017.07.012