AQUACULTURE ENVIRONMENT INTERACTIONSAquacult Environ Interact

Vol. 9: 331–346, 2017https://doi.org/10.3354/aei00238

Published September 22

INTRODUCTION

Aquaculture facilities contribute substantially tothe world fish supply and are increasing in abun-dance worldwide (Naylor et al. 2000). In 2014, overhalf of the fish that humans consumed were pro-duced through aquaculture, highlighting the impor-tance of aquaculture as a reliable food source forincreasing populations (FAO 2016). Aquaculture isimportant, but the wastes and nutrients produced bythese facilities can pose threats to coastal environ-

ments (Nogales et al. 2011, Jiang et al. 2013). As aresult, monitoring efforts are routinely needed tounderstand potential impacts. Most aquaculturemonitoring efforts are part of required environmentalimpact assessments that may include collectingmeasurements of water quality, nutrient concentra-tions, organic matter outputs, and residual chemicalsand bacteria that affect the product quality (Ham-brey 2009). In addition, indicator species assays arecommonly used to detect a finite number of knownpathogens (Hernández et al. 2009, Zhou et al. 2014).

© The authors 2017. Open Access under Creative Commons byAttribution Licence. Use, distribution and reproduction are un -restricted. Authors and original publication must be credited.

Publisher: Inter-Research · www.int-res.com

*Corresponding author: aapprill@whoi.edu

Impact of prawn farming effluent on coral reefwater nutrients and microorganisms

Cynthia Becker1,2, Konrad Hughen1, Tracy J. Mincer1, Justin Ossolinski1, Laura Weber1, Amy Apprill1,*

1Department of Marine Chemistry and Geochemistry, Woods Hole Oceanographic Institution, Woods Hole, MA 02543, USA2Department of Biology, Ithaca College, Ithaca, NY 14850, USA

ABSTRACT: Tropical coral reefs are characterized by low-nutrient waters that support oligo -trophic picoplankton over a productive benthic ecosystem. Nutrient-rich effluent released fromaquaculture facilities into coral reef environments may potentially upset the balance of these eco-systems by altering picoplankton dynamics. In this study, we examined how effluent from a prawn(Litopenaeus vannamei) farming facility in Al Lith, Saudi Arabia, impacted the inorganic nutrientsand prokaryotic picoplankton community in the waters overlying coral reefs in the Red Sea.Across 24 sites, ranging 0−21 km from the effluent point source, we measured nutrient concentra-tions, quantified microbial cell abundances, and sequenced bacterial and archaeal small subunitribosomal RNA (SSU rRNA) genes to examine picoplankton phylogenetic diversity and commu-nity composition. Our results demonstrated that sites nearest to the outfall had increased concen-trations of phosphate and ammonium and elevated abundances of non-pigmented picoplankton(generally heterotrophic bacteria). Shifts in the composition of the picoplankton community wereobserved with increasing distance from the effluent canal outfall. Waters within 500 m of the out-fall harbored the most distinct picoplanktonic community and contained putative pathogenswithin the genus Francisella and order Rickettsiales. While our study suggests that at the time ofsampling, the Al Lith aquaculture facility exhibited relatively minor influences on inorganic nutrients and microbial communities, studying the longer-term impacts of the aquaculture efflu-ent on the organisms within the reef will be necessary in order to understand the full extent of thefacility’s impact on the reef ecosystem.

KEY WORDS: Aquaculture · Litopenaeus vannamei · Oligotrophic · Microbial community · Coral reef · SSU rRNA gene · Francisella spp.

OPENPEN ACCESSCCESS

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There has been much less effort towards monitoringhow entire bacterial and archaeal communitiesrespond to the influx of aquaculture waste. A moreinclusive method that uses comparative phylogeneticanalyses to examine how picoplanktonic communi-ties respond can help deepen this understanding.

Microorganisms, including Bacteria, Archaea, andphytoplankton, are critical to the coastal marine envi-ronment and actively participate in biogeochemicalcycling of nutrients and organic matter (Kirchman etal. 2007, DeLong 2009). Microbes are sensitive toeutrophication and pollution-based changes in sea-water, with some cells exhibiting enhanced or re -duced growth under these conditions (dos Santos etal. 2011, Xiong et al. 2015). Studies have shown thatin oligotrophic waters, continual enrichment ofnitrate and phosphate alters the native bacterial com-munity composition (Chen et al. 2016, Dong et al.2017). As a result, microorganisms may be able toserve as sensitive indicators of change, especially inoligotrophic environments where the magnitude ofnutrient and organic matter inputs from aquaculturecould be much higher than natural inputs to the envi-ronment. For example, the naturally oligotrophiccoral reef waters of the Red Sea feature very lownutrient concentrations of 0.05−0.1 µM phosphate,<0.1 µM ammonium, and <0.3 µM nitrate+nitrite(Furby et al. 2014). Therefore, water-column samplesfrom coral reefs located within the Red Sea are idealfor identifying how anthropogenic inputs from aqua-culture facilities perturb the low-nutrient system andimpact the bacterial and archaeal picoplankton com-munities.

Nutrient pollution and eutrophication from aqua-culture are important problems affecting tropicalcoral reef ecosystems that reside in oligotrophicwaters. Specifically, aquaculture runoff introducesammonium, phosphate, and organic solids into thesurrounding water. Studies have shown that fishfarm runoff can reduce the survivorship of juvenilecorals (Villanueva et al. 2005) and impair coral repro-duction (Loya et al. 2004), as well as impact coral-associated microbes (Garren et al. 2008, 2009, Camp-bell et al. 2015). Studies also demonstrate that theplanktonic microbial community, which is easier tosample and analyze than coral-associated microbes(e.g. Apprill et al. 2016), shows similar communitychanges in response to environmental aquaculturepollution (Sousa et al. 2006, Garren et al. 2008,Fodelianakis et al. 2014, Xiong et al. 2015). Forexample, in aquaculture environments such as acoastal shrimp pond in southeast China (Wei et al.2009) and a fish farm north of Crete, Greece (Fo -

delianakis et al. 2014), the seawater microbial com-munities had reduced phylogenetic diversity andexperienced overall shifts in community composition.Increases in Proteobacteria, free-living bacteria, andvirus-like particles were also noted in the oligo -trophic reef waters of the Philippines, correlatingwith organic nutrient enrichment caused by a fishfarm (Garren et al. 2008). These often site-specificalterations to the planktonic microbial community byaquaculture speak to the complexity of these oligo-trophic ecosystems. It also exemplifies the need forcontinued assessments of these impacts, especially inunderstudied areas such as the eastern Red Sea.

The National Aquaculture Group, formerly knownas the National Prawn Company, is a coastal aqua-culture facility located next to coral reefs in the east-ern Red Sea, near the city of Al Lith, Saudi Arabia. Itis one of the largest desert aquaculture facilities inthe world and covers approximately 250 km2. From2008 to 2010, our team examined the Red Sea marineenvironment to identify potential sources of putativepathogens that were associated with the presence ofharmful coral lesions (Apprill et al. 2013, Furby et al.2014). As part of this study, we examined whetherthe effluent from the National Prawn Company aquaculture facility could be a potential source ofnutrients and pathogens to the surrounding environ-ment. At the time of the sampling in 2009, the facilitywas hatching and rearing approximately 15 000 tonsof white prawn Litopenaeus vannamei annually inponds covering a total surface area of 2800 ha(https://web.archive.org/web/20091130220933/http://www.robian.com.sa:80/home.html; see also www.naqua.com.sa). Since the time of sampling, the facility expanded to include multiple sea cages andmany more shrimp farms and produces upwards of100 000 tons of marine products annually, includingshrimp, sea cucumber, and sea bass (www.naqua.com.sa). Furthermore, Saudi Arabia has plans toexpand its aquaculture industry, with multiple in -vestments in new facilities (Mon Chalil 2015). In thecontext of continuous expansions of the aquacultureindustry, it is important to understand the extent towhich this industry may threaten the adjacent deli-cate reef ecosystem. In this study, we aimed to assessthe impact of the effluent from this aquaculture facil-ity on the surrounding oligotrophic reef environmentby examining the inorganic nutrient concentrationsand microbial communities in an area extendingnearly 22 km from the outfall. We hypothesized thatconcentrations of inorganic nitrogen and phosphoruswould be elevated at the outfall, a distinct microbialcommunity would reside there, including known

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pathogens, and that this impact would diminish withincreasing distance from the outfall.

MATERIALS AND METHODS

Sampling

Sampling occurred in the eastern Red Sea, sur-rounding the runoff from the National Prawn Com-pany aquaculture facility in Al Lith, Saudi Arabia(Fig. 1a). Seawater was sampled from 24 stations sur-rounding the aquaculture facility using a directional-transect grid pattern (Fig. 1b,c) from October 9 to 12,2009, during 10:00−16:00 h. The sampling patternextended in 5 transects away from the outfall pointsource: north, northwest, west, southwest, and southalong the coastline (Table A1 in the Appendix). Sam-pling occurred first at the mouth of the outfall, andthen was spaced 0.5−21.7 km along the 5 transects(Fig. 1). Seawater was sampled at a 10 m depth,which was just above the coral reef for the shallowersites, into 20 l acid-washed carboys. Inorganic nutri-ents and microbial abundance samples were col-lected and processed as previously outlined in Furbyet al. (2014). Briefly, for inorganic nutrients, 150 mlpolypropylene acid-washed bottles were filled withseawater and frozen at −20°C. Samples (1 ml) for cellcounts were fixed in 1% (v:v) paraformaldehyde(final concentration) and placed in cryovials in liquid

nitrogen for 3 wk, then frozen at −80°C. Seawater forDNA analyses was stored on ice for no more than 4 hbefore it was filtered onto 0.22 µm Durapore mem-brane filters (142 mm) (Millipore) with a peristalticpump. Filters were then frozen in liquid nitrogen.

Nutrient analysis

Nutrients were analyzed as outlined in Furby et al.(2014). In summary, dissolved concentrations ofNH4

+, NO3−+NO2

−, NO2−, PO4

3−, and silicate weredetermined with a continuous segmented flow sys-tem including a Technicon AutoAnalyzer II (SEALAnalytical) and an Alpkem RFA 300 Rapid Flow Ana-lyzer. NO3

−+NO2− and NO2

− were measured accord-ing to Armstrong et al. (1967). An adjusted molyb -denum blue method was used to measure PO4

3−

(Bernhardt & Wilhelms 1967). The indophenol bluemethod was used to measure concentrations of NH4

+

(USEPA 1983), and validated using a method devel-oped by Holmes et al. (1999).

Direct cell counts

Microbial cell counts were enumerated using theflow cytometry methods described in Furby et al.(2014). To summarize, the preserved samples wereanalyzed using stained and unstained methods to

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Fig. 1. (a) Location of the aquaculture facility in Al Lith, Saudi Arabia (yellow pin), in the eastern Red Sea. Gray arrow: the pre-vailing surface currents that move S to N, primarily along the eastern coast. (b) The 24 sites that were sampled along 5 tran-sects extending from the aquaculture outfall up to 21.7 km from the outfall. (c) Inset: a more detailed map of the outfall (Site 8)and nearby sites. Images reproduced according to Google permissions and incorporate data from NOAA, US Navy, National

Geospatial-Intelligence Agency, General Bathymetric Chart of the Oceans, DigitalGlobe, and US Geological Survey

Aquacult Environ Interact 9: 331–346, 2017

determine the number of pigmented and non-pig-mented cells within each sample. The aliquots ofsample for the unstained method were run on anEPICS ALTRA flow cytometer (Beckman Coulter) todetermine abundance of Cyanobacteria (Prochloro-coccus and Synechococcus) and small eukaryoticphytoplankton (picoeukaryotes). The aliquot of sam-ple for staining was prepared by diluting the sample1:10 into a 30 mM (final concentration) potassium cit-rate buffer solution, and staining with Sybr Green I(1:5000 final dilution of initial stock) (MolecularProbes) for a duration of 2 h in the dark at 4°C. Exci-tation of the fluorescent stain was accomplishedusing a laser operating at a wavelength of 488 nm onthe same EPICS ALTRA flow cytometer, and thisallowed for enumerating picoplankton (Bacteria andArchaea) on the basis of DNA staining (Sybr Green Igreen fluorescence), chlorophyll, phycoerythrin, for-ward scatter, and 90° side scatter signatures. Pro -chlorococcus cell counts from the unstained methodwere subtracted from total prokaryotic cells to obtaincounts of non-pigmented picoplankton. FlowJo soft-ware (v.6.3.3, Tree Star) was used for off-line dataanalysis.

DNA analysis

The filters were cut into quarters, and DNA wasextracted from one of the quarters using a bead beat-ing method combined with a sucrose-lysis extractionand spin-column separation. Briefly, 0.1 mm glassbeads were used to homogenize cellular biomass col-lected on the filters for 10 min in a solution of 875 µlsucrose-EDTA lysis buffer (0.75 M sucrose, 20 mMEDTA, 400 mM NaCl, 50 mM Tris) and 100 ml of 10%sodium dodecyl sulfate. This was followed by a Pro-teinase K digestion at 55°C for 4 h, and separation ofthe DNA using the spin columns supplied by theDNeasy kit (Qiagen) (Santoro et al. 2010). The DNAsamples were individually amplified with the 515F(5 -GTG CCA GCM GCC GCG GTA A-3 ) and806RB primers (5 -GGA CTA CNV GGG TWT CTAAT-3 ), with the modified reverse primer designed toenhance the detection of different SAR11 clades(Apprill et al. 2015). The primers were designed sim-ilar to Kozich et al. (2013) and each included a unique8 bp barcode, 10 bp pad, and 2 bp link in addition tothe primers described above. PCR reactions werecarried out in a Bio-Rad thermocycler using triplicate25 µl volumes for each sample. Each reaction in -cluded 1.25 U GoTaq Flexi DNA Polymerase (Pro -mega), 5× Colorless GoTaq Flexi Buffer, 2.5 mM

MgCl2, 200 µM dNTP mix (Promega), 200 nM of thecorresponding barcoded primer, and 1−4 ng of gen -omic DNA template. The reaction conditions were asfollows: initial denaturation for 2 min at 95°C, fol-lowed by an iteration of 20 s at 95°C, 15 s at 55°C and5 min at 72°C for 25−28 cycles, and a final extensionstep for 10 min at 72°C. Five µl of the reaction prod-ucts were run on a 1% agarose/TBE gel containingthe HyperLadder 50 bp DNA ladder (generally 5 ngµl−1) (Bioline). After pooling the triplicate reactionsper sample, the PCR products were purified with theQIAquick Purification Kit (Qiagen). The sampleswere quantified using the Qubit 2.0 Fluorometer withthe dsDNA High Sensitivity Assay (Life Technolo-gies). The PCR products were then combined intoequimolar ratios and processed for sequencing using250 bp paired-end MiSeq (Illumina) at the W. M.Keck Center for Comparative and Functional Gen -omics at the University of Illinois. Raw sequence datawere deposited into the National Center for Biotech-nology Information (NCBI) Sequence Read Archive(SRA) under accession number PRJNA357506.

Sequence analysis

Sequence data were filtered and analyzed usingmothur v.1.36.1 (Schloss et al. 2009). This includedconstructing contigs, filtering out long amplicons(over 255 bp), and removing chimeras detected usingde novo UCHIME v.4.2.40 (Edgar et al. 2011). Thetaxonomic assignment for each sequence was per-formed in mothur using the SILVA SSU referencedatabase (v.123) and the k-nearest neighbor algo-rithm with an 80% cutoff. The number of small sub-unit ribosomal RNA (SSU rRNA) sequences per sam-ple varied between 266 and 55 182 and the datasetwas therefore subsampled to a depth of 10 200sequences per sample, resulting in the loss of onlySample 20 (Appendix 1). Operational taxonomicunits (OTUs) for each sample were generated usingthe minimum entropy decomposition (MED) cluster-ing algorithm (Eren et al. 2015). MED further re -duced the sequence reads to between 8853 and 9538sequences per sample (Appendix 1).

Graphical and statistical analyses

Ocean Data View software (v.4.7.8, 64 bit) (Schlit -zer 2002) was used to create contour plots of nutri-ents and microbial abundances using data-inter -polating variational analysis (DIVA) gridding (40 × 40

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scale length). PRIMER-E 7 (v.7.0.11, Quest Research)was used to compare the composition of OTUs ateach sampling site. The data were square-root trans-formed, compared using Bray-Curtis similarity, andplotted using non-metric multidimensional scaling(nMDS) to compare microbial community structureacross samples. Information regarding proximity tothe outfall was superimposed onto the symbols foreach sample in the nMDS plot. In addition, bar plotswere generated in Excel for Mac 2011 (v.14.6.9,Microsoft) to illustrate microbial community compo-sition by plotting the relative percent abundance oftaxonomic groups of Bacteria and total Archaea.

Alpha diversity metrics of microbial communities ateach site were computed using the plot_richnessfunction in the phyloseq (v.1.16.2) and ggplot2(v.2.1.0) R packages in RStudio (v.0.99.902) (Wick-ham 2009, McMurdie & Holmes 2013). Specific metrics plotted include ‘observed’ (observed rich-ness), ‘Chao1’ (estimator of richness), and ‘invsimp-son’ (inverse Simpson index of diversity). Differen-tially abundant OTUs between the outfall and othersites were obtained using DESeq2 (v.1.12.4) in RStu-dio (Love et al. 2014). Specifically, OTU sequencecount data was compared between the outfall siteand 6 different distance groups away from the outfallthat encompassed the other sites (0.5−1.5, 2.5−3,4.5−5.3, 9−10.1, 14.5−15.2, and 20−21.7 km). Signifi-cant differential abundance was determined inDESeq2 using the adjusted p-value (p < 0.05). Boxplots of relative abundance data for significantlyenriched (at the outfall) OTUs were created inPRIMER-E 7 (v.7.0.11).

RESULTS

Nutrients

Nutrient concentrations were generally similaracross most of the sites spanning 0−21.7 km from theoutfall (Fig. 2), with the exception of ammonium andphosphate, which were elevated at the outfall by5−75 times and 4−14 times, respectively, compared tothe other sites (Fig. 2a,d). Ammonium was 0.60 µM atthe outfall and below 0.12 µM (Site 19) at all othersites (Fig. 2a,j). The concentration of phosphate at theoutfall was the highest measured in the study, at0.67 µM, while all other sites were lower, below0.17 µM (Site 7) (Fig. 2d,m). Concentrations of nitrite,nitrate+nitrite, and silicate were not elevated nearthe outfall, and were similar in concentration to themore distant sites (Fig. 2b,c,e,k,l,n). Over the study

area, the combined nitrate+nitrite concentrationsranged from undetectable to 0.87 µM, nitrite rangedfrom 0.02 to 0.11 µM, and silicate ranged from 0.08 to1.64 µM (Fig. 2b,c,e).

Microbial abundances

Cell counts of microbial groups were measured atall 24 sites (Fig. 2f−i), and there were no clear pat-terns in cell abundances, either elevated or depleted,directly at the outfall. Concentrations of non-pigmen -ted picoplankton, a proxy for heterotrophic Bacteria,Archaea, and non-pigmented photoheterotrophicBacteria, were high at the outfall (1.5 × 106 cells ml−1)as well as at Sites 19, 17, 10, and 11 (1.3 to 1.5 × 106

cells ml−1), which are all between 3 and 5 km awayfrom the outfall (Fig. 2f,o). Concentrations were up to9.3 × 105 cells ml−1 lower at the remaining sites,which ranged from 5.8 × 105 to 1.2 × 106 cells ml−1.Synechococcus spp. were depleted directly at theoutfall (1.5 × 105 cells ml−1) compared to nearby Sites7 and 9 that are ≤1.5 km away (2.0−2.1 × 105 cellsml−1) (Fig. 2q). Synechococcus spp. were most abun-dant at sites 2.5 km from the outfall (Sites 5 and 12;3.0−3.2 × 105 cells ml−1; Fig. 2q). Abundances ofProchlorococcus spp. varied from 2.4 × 104 to 6.4 ×104 cells ml−1, with no major changes observed overthe sampling area (Fig. 2g). The abundance ofpicoeukaryotes ranged from 2.1 × 103 to 1.2 ×104 cells ml−1 (mean: 4.6 × 103 cells ml−1), and werealso consistent across the sampling area (Fig. 2i).

Microbial community phylogenetic diversity

Alpha diversity indices of bacterial and archaealOTUs based on SSU rRNA gene sequences showedsome variability between the sites. The observedcommunity richness, or number of observed OTUs,ranged between 225 and 357 OTUs, and richness atthe outfall site fell near the middle of this range, at291 (Fig. 3a). Two sites, Site 25 (9 km from outfall)and Site 6 (1.5 km from outfall), contained microbialcommunities of lower richness, at 225 and 240 OTUs,respectively. The Chao1 estimator of richness pro-duced patterns similar to the observed richness(Fig. 3a,b), indicating that the depth of sequencingutilized was appropriate for the study. When the sam-ples were organized by distance from the outfall,there appeared to be a potential increase in esti-mated richness with increasing distance to ~5 km.Again, Sites 6 and 25 had lower predicted richness

335

Aquacult Environ Interact 9: 331–346, 2017336

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Becker et al.: Prawn farming impact on coral reef waters 337

Fig. 2 (continued)

Aquacult Environ Interact 9: 331–346, 2017

(Fig. 3b). The inverse Simpson index of diversity alsoindicates community evenness (Fig. 3c), and itranged from low diversity and evenness, at 3.58 (Site25, 9 km from the outfall), to higher diversity andevenness, at 31 (Site 13, 20 km from the outfall), witha mean of 15. Even though Site 6 was low in bothobserved and estimated richness (Fig. 3a,b), it wasnot low in diversity relative to the other sites, indica-ting that Site 6 had a more even microbial commu-nity. In terms of diversity, the outfall, with an inverseSimpson index of 17.5, was similar to the other sites.

Microbial community composition

The SSU rRNA gene sequences were dominatedby Cyanobacteria and Alphaproteobacteria andshowed similar trends in composition across the sites(Fig. 4). Two sites, 24 and 25, were made up of mostlyCyanobacteria, comprising 60 and 75% of total se-quences, respectively. The outfall (Site 8) was similarto most sites, except that it had 3 times as muchFlavobacteria as all other sites (15.6% compared to amean of 4.7% for the other sites) (Fig. 4). An nMDSanalysis provided a spatial representation of commu-

nity composition resemblance between sites (Fig. 5).Again, in this analysis, the southern Sites 24 and 25were separated from the group, supporting how mi-crobial communities at these sites were distinct frommost of the other sites. Coastal Site 6 was also sepa-rated, both from the entire group of sites, and alsofrom the other sites 0.5−1.5 km (Fig. 5) from the out-fall. In general, the arrangement of sites in the nMDSplot corresponds to actual distance from outfall,demonstrating that the bacterial and archaeal com-munities shifted in composition with increasing dis-tance away from the effluent outfall. The 0.5−3 kmgroup plotted closer to the outfall than the 4.5−10.1 km distance group. In addition, the 14.5−21.7 km group was even farther from the outfall pointin the nMDS plot (Fig. 5). The outfall site is distinctlyseparate in the plot, indicating that there are taxawithin the community that are unique to the outfall.

Differentially abundant outfall bacteria

Microbes indicative of the outfall effluent were ex-amined using the SSU rRNA gene sequence countdata, and 22 OTUs were significantly elevated or de-

338

Fig. 3. Measures of alpha diversity based on bacterial and archaeal small subunit ribosomal RNA (SSU rRNA) genes at eachsampling site: (a) community richness (e.g. number of operational taxonomic units), (b) Chao1 estimator (bars: 95% confidence

intervals), and (c) inverse Simpson index. Data are organized into groups based on distance from the outfall

Becker et al.: Prawn farming impact on coral reef waters

pleted at the outfall when compared to the 6 distancegroupings (0.5−1.5, 2.5−3, 4.5−5.3, 9−10.1, 14.5−15.2,and 20−21.7 km) (Fig. 6, Table 1). Of these, 7 OTUswere significantly elevated at the outfall (Fig. 6).These included sequences classifying as Francisellaspp., Caedibacter spp., uncultured Gamma proteo -bacteria, members of the NS4 Marine Group, uncul-tured Rickettsiales, uncultured Flavo bacteriaceae,and uncultured Cryomorphaceae (Fig. 6a−g). Se-quences of those OTUs enriched at the outfall werefound in lower abundances at the more distant sitegroupings, and were significantly different at manyof these groups (p < 0.05; Fig. 6). For OTUs 622 (Fran-cisella spp.), 705 (Caedibacter spp.), and 1653 (uncul-tured Gammaproteobacteria), se quence counts weresignificantly lower at all distances compared to theoutfall (Fig. 6a−c). Sequence counts for OTUs 1743(NS4 Marine Group) and 1342 (uncultured Rickett -siales) were significantly lower at all distance groupsexcept for the closest one, 0.5−1 km from the outfall

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Fig. 4. Relative abundances of small subunit ribosomal RNA (SSU rRNA) gene sequences organized by taxonomic class foreach site. Sites are organized by distance from outfall, with Sample 8 (outfall) on the far left and Sample 21 (21.7 km from

Site 8) on the far right

Fig. 5. Non-metric multidimensional scaling analysis of bac-terial and archaeal community composition at each studysite based on small subunit ribosomal RNA (SSU rRNA)gene sequences. Relative abundance data were square-roottransformed and the resemblance of community composi-tion was determined using Bray-Curtis similarity. Sites aregrouped by distance from the outfall and the numbers indi-

cate site. The 2-D stress of the solution is 0.06

Aquacult Environ Interact 9: 331–346, 2017

(Fig. 6d,e). Sequence counts for OTU 391 (unculturedFlavobacteriaceae) were significantly different fromthe outfall for the 4 farthest distance groups (4.5−5.3,9−10.1, 14.5–15.2, and 20–21.7 km), but not the 2closest distance groups (Fig. 6f). Sequence counts forOTU 2711 (un cultured Cryomorphaceae) were signif-icantly distinct from the outfall at 2 of the farther dis-tance groups (9−10.1 and 20−21.7 km) (Fig. 6g). Theother 15 significantly differentially abundant OTUswere significantly en riched or depleted in 3 or fewerdistant groups, when compared to the outfall, as indi-cated by the positive and negative log2 fold change(Table 1). Out of the 15 significantly enriched OTUs,11 were from the taxonomic class Flavobacteria(Table 1), the class of Bacteria found at higherrelative abundance at the outfall compared to theother sites (Fig. 4).

DISCUSSION

This study analyzes multiple factors, includingnutrient concentrations, microbial cell abundances,and the fine-scale taxonomy and composition of the

bacterial and archaeal seawater communities, toexamine the impact of an effluent point source from alarge aquaculture facility on oligotrophic coral reefswithin the Red Sea. Although our results representdata from 2009 and were collected prior to recentexpansions of the facility, they show a distinct eleva-tion of ammonium and phosphate and an alteredmicrobial community structure at the outfall, withsubtler differences within microbial community com-position as distance from the outfall increases.

The elevated levels of ammonium and phosphateat the outfall site were consistent with findings ofaquaculture impacts in other studies. Biao et al.(2004) found elevated inorganic nutrient concentra-tions, including ammonium and phosphorus, in ashrimp farm outlet creek that flowed from shrimpponds to the Yellow Sea. In that study, changes inammonium reached 4.7 µM, much greater than inour study, whereas the magnitude of change in inor-ganic phosphorus concentrations was 0.26 µM, lowerthan that measured in our study (0.5 µM). In a studyof fish cages in the eutrophic environment of theXiangshan Bay, China, Xiong et al. (2015) observedoverall increases in the concentrations of dissolved

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Fig. 6. Box-and-whisker plots of sequence counts for the 7 operational taxonomic units (OTUs) that were significantly enrichedat the outfall site: (a) Francisella spp., (b) Caedibacter spp., (c) uncultured Gammaproteobacteria, (d) NS4 Marine Group, (e)uncultured Rickettsiales, (f) uncultured Flavobacteriaceae, and (g) uncultured Cryomorphaceae. *Distance groups with signif-icantly depleted sequence counts compared to sequence counts at the outfall (p < 0.05). The outfall includes 1 sample (indi-cated by single line) and the other distance groups include 3−5 samples. In each plot, middle line denotes median, box outlines

upper and lower 25% quartiles, and whiskers denote maximum and minimum values

Becker et al.: Prawn farming impact on coral reef waters

inorganic nitrogen and phosphate atfish cages relative to a reference sitethat was 8 km away. The magnitudeof increase of dissolved inorganicnitrogen was approximately 2.4 µM,much higher than any concentrationmeasured in our study. In contrast,while overall phosphate concen -trations were higher within theeutrophic bay, the increase in phos-phate at the fish farm (0.1 µM) waslower than the increase measured inour study (0.5 µM). Although themagnitude of changes varied amongstudies, the ubiquitous increase inseawater nutrient concentrations inareas supporting aquaculture facili-ties suggests that they can be a sourceof nutrient enrichment to both eu -trophic and oligotrophic environ-ments. This comparison further sug-gests that the elevated nutrientconcentrations may be attributed toanimal waste products generated atthe aquaculture facility. Since thetime of sampling in 2009, the Al Lithaquaculture facility has expandedconsiderably to include more shrimpfarms and sea cages. If these inor-ganic nutrient concentrations wereamong the highest recorded in theRed Sea in 2009, we would hypothe-size that nutrient levels will have onlyincreased as a result of the expan-sions, further threatening the delicatereef ecosystem.

In the study presented here, wefound it surprising that the effluentnutrient signal diminished so rapidlyjust 500 m away from the outfall. Thiscould be related to the oligotrophicnature of the Red Sea waters, inwhich generally low-concentration orlimiting nutrients are quickly mixedand diluted into the surroundingwaters, or are rapidly assimilated bybacteria and other planktonic organ-isms that recycle these nutrients andincorporate them into microbial bio-mass. Although detailed circulationdata for the Red Sea is scant, thestudy area features a buoyancy-dri-ven boundary current that moves

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Aquacult Environ Interact 9: 331–346, 2017

generally from south to north, which may also becontributing to the incorporation of nutrients into thesurrounding waters (Eshel & Naik 1997). Anotherfactor may be the length of the effluent canal. Biao etal. (2004) found diminishing concentrations of allmeasured inorganic nutrients along an outlet canalthat ex tended from 3 shrimp ponds to the Yellow Sea,over a distance of 11 km. The effluent canal of theNational Prawn Company facility runs the length ofthe shrimp pond area, over 20 km long, and may be acting as a potential biological buffer where higherlevels of nutrients are consumed before reaching theoligotrophic waters.

Of the microbial cells enumerated, non-pigmentedpicoplankton were the only cell groups found to beelevated at the outfall, as well as at nearby sites.Non-pigmented picoplankton are primarily hetero-trophic Bacteria and Archaea as well as non- pigmented photoheterotrophic Bacteria, and theirabundance is often related to the organic carbonavailability (Jumars et al. 1989), which was likely ele-vated as a result of shrimp organic wastes in theeffluent. Although organic carbon was not measuredhere, preventing a complete assessment, a study ofbacterial communities below a fish farm cage foundincreased abundances of heterotrophic bacteria as aresult of total organic matter enrichment (La Rosa etal. 2004). This suggests the elevated abundances ofnon-pigmented picoplankton at the outfall may bedue to populations of these cells residing in theorganic-rich effluent, likely confirming the presenceof increased organic matter. Indeed, future studies ofaquaculture effluent should include quantification ofparticulate and dissolved organic carbon.

One particular strength of this study was the ex -amination of the microbial SSU rRNA sequencesfrom general bacterial and archaeal primers, whichallowed for a more holistic examination of the com-munities compared to cultivation-dependent or indi-cator microbial assays, such as loop-mediated iso -thermal amplification assays that detect knownbacterial pathogens (Zhou et al. 2014). An example ofone of the benefits of using cultivation-independenttechniques to study microbial communities withinthe environment is that it allowed us to produce newknowledge of potential indicator bacterial taxa thatmay be originating from shrimp aquaculture. Wefound alterations in the entire microbial communitycomposition with increasing distance away from theaquaculture effluent point source. This finding isconsistent with studies that found changes in themicrobial communities between treated wastewaterrunoff and the seawater surrounding coral reefs in

Florida (Campbell et al. 2015) and in the Red Sea(Ziegler et al. 2016). It also confirms other studyresults that found alterations in bacterial communi-ties in oligotrophic areas subject to aquaculture (fishfarm) effluent (Garren et al. 2008, Fodelianakis et al.2014). In our study, 22 groups of bacteria were iden-tified as being significantly elevated or depleted atthe outfall site. Of these, 7 were elevated at the out-fall of the effluent canal when compared to multipledistances, suggesting that they potentially originatedat the aquaculture facility. Of these enriched groups,2 OTUs, classifying as Francisella spp. and uncul-tured Rickettsiales, are related to known pathogens.Francisella spp. have been implicated as pathogensfor a wide taxonomic diversity of mammals and fish,as well as free-living cells (Sjödin et al. 2012). Patho-genic Francisella generally target marine organisms,causing disease in cod (Olsen et al. 2006), tilapia(Mauel et al. 2007), and giant abalone (Kamaishi etal. 2010). In addition, Francisella spp. can also impacta wide diversity of land mammals, including humans,through arthropod vectors or infected water (Pérez etal. 2016). It is likely that the infection breadth ofFrancisella spp. is highly underestimated (Birkbecket al. 2011), and the significant occurrence of Fran-cisella spp. at the shrimp aquaculture outfall maysuggest that Francisella spp. originated in the shrimpponds. Some pathogenic species, including F. noa -tunensis (cod pathogen) and F. tularensis (humanpathogen), likely persist poorly in the environmentwithout a host (Duodu & Colquhoun 2010). Despitethis, Francisella spp. have been isolated in seawatersamples from around the world (Barns et al. 2005,Berrada & Telford 2010, Duodu et al. 2012). Somepathogenic Francisella strains may interact with single-celled eukaryotes, allowing them to persistsuccessfully in the environment (Verhoeven et al.2010). While presence and abundance of single-celled eukaryotes were not measured in this study,they generally feed on bacteria, and increased levelsof heterotrophic bacteria at the effluent outfall mayhave provided a favorable environment for eukary-otic Francisella spp. hosts. The other putative patho-gen detected in this study was uncultured Rick-ettsiales. While not every Rickettsiales bacterium ispathogenic, these bacteria belong to an order that ischaracterized by having both obligate intracellularand free-living lifestyles. Rickettsiales can invadearthropod hosts (Darby et al. 2007), and in fact, thefirst marine Rickettsiales pathogen to be character-ized, ‘Candidatus Hepatobacter penaei’, was origi-nally isolated from Penaeus vannamei, and sub -sequently found in both an arthropod and crustacean

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as well as a commonly cultured shrimp in the westernhemisphere (Nunan et al. 2013). Caedibacter spp.encompass another interesting group of bacteria ele-vated at the outfall. While this bacterium is notpatho genic, this genus comprises species that areunique endosymbionts of paramecia (Beier et al.2002). Paramecia have been isolated from fresh,brackish, and seawater environments where theycan prey on other bacteria and algae (Fokin et al.1999, Fokin 2010). While little information on specificassociations of paramecia within shrimp aquacultureexist, the outfall of the effluent canal was character-ized by increased counts of heterotrophic bacteria,and may have hosted an environment favorable tothe algae- and bacteria-consuming paramecia, whichcould account for the increase in Caedibacter spp. atthe outfall.

Other bacteria elevated at the outfall includedcommon seawater bacteria, including unculturedGammaproteobacteria, uncultured Flavobacteria -ceae, NS4 Marine Group, and uncultured Cryomor-phaceae. The Flavobacteriaceae are a large family ofmarine bacteria, and this family includes some spe-cies that are associated with phosphorus and nitro-gen enrichment as well as shrimp aquaculture(Maeda et al. 2002, Abell & Bowman 2005). NS4 Mar-ine Group and uncultured Cryomorphaceae are alsocommon bacteria in seawater, but less is knownabout their physiology (Alonso et al. 2007, Bowman2014). While some bacteria were found at higherabundances at the outfall, others were significantlydepleted at the outfall. For example, 3 OTUs belong-ing to the SAR116 clade of Alphaproteobacteria weredepleted at the outfall. The SAR116 clade has beenisolated from oligotrophic waters globally, such asthe Sargasso Sea and the North Pacific SubtropicalGyre (Mullins et al. 1995, DeLong et al. 2006). Whilethe Red Sea is naturally oligotrophic, the outfall sitewas characterized by nutrient enrichment. It is likelythat the more eutrophic environment of the outfallwas poorly suited for bacteria that thrive in oligo -trophic waters, such as the SAR116 clade, but pro-vided an ideal environment for other bacteria such asthose from the class Flavobacteria and Francisellaspp., as evidenced by the significant changes insequence counts for those groups. In this way, thenutrient enrichment from the aquaculture facilityappears to exert a bottom-up control on the microbialdiversity near the effluent outfall.

Two limitations of this study included a lack of tem-poral resolution as well as site replication. These limitations prevented us from utilizing statistical ap -proaches to compare the outfall nutrients and micro-

bial cell abundances to the other sites. We were alsonot able to understand the consistency of the impactto the microbial communities over time, because oneseawater sample was collected directly at the out-fall. In the future, we recommend sampling fartherup the effluent canal, or obtaining samples from theaquaculture pools to enhance our understanding ofthe microbial processes occurring within the effluentcanal before the effluent reaches the Red Sea.

CONCLUSIONS

In our 2009 assessment of the impact of theNational Aquaculture Group facility near Al Lith,Saudi Arabia on the microbial and biogeochemicalcomposition of the eastern Red Sea, we found thatthe outfall site showed elevated concentrations ofammonium and phosphate, along with changes inthe microbial communities, including the presence ofthe potential pathogens Francisella spp. and Rick-ettsiales. The impacts of the effluent were morelocalized than hypothesized, with elevated nutrientsand statistically significant microbial communityalterations restricted to only the outfall site anddiminishing within 500 m, likely related to the highlyoligotrophic nature of these waters. Aside from thisseemingly localized impact, we also noticed a shift inthe microbial communities with increasing distancefrom the outfall across the entire study area. Theimpact of the aquaculture facility on the entire coralreef ecosystem was not addressed here, but our datafor the waters overlying the reef near the effluentcanal suggests that this ecosystem may indeed beimpacted by the aquaculture effluent, and thesereefs and their water quality should be monitored inthe future. This study expands on the existing knowl-edge of the impacts aquaculture imposes on oligo -trophic coral reef ecosystems, although since 2009,the increased aquaculture output in the eastern RedSea may have altered the observed impacts. As theglobal aquaculture industry continues to expand tomeet the demands of population growth, studies ofthis nature will be critical in order to assess theimpacts that this industry imposes on the surround-ing marine environment, especially in oligotrophicareas harboring sensitive coral reef ecosystems.

Acknowledgements. We thank Whitney Bernstein, KathrynFurby, Jesse Kneeland and the crew of the M/V ‘DreamIsland’ for sample collections and logistical support. Wethank Karen Selph of the University of Hawai‘i School ofOcean and Earth Science and Technology (SOEST) flow

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cytometry facility for cell counts, Joe Jennings of OregonState University for inorganic nutrient analysis, and C.Wright and the University of Illinois W. M. Keck Center forComparative and Functional Genomics for sequencing. Thisresearch was supported by a Woods Hole OceanographicInstitution (WHOI) Ocean Life Institute postdoctoral scholarfellowship to A.A., the Semester at WHOI Program support-ing C.B., and Award No. USA 00002 to K.H. made by KingAbdullah University of Science and Technology (KAUST).

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Sample Distance No. of Sub- No. of No. of Chao1 Inverse site to outfall reads sampled reads after OTUs Simpson

(km) reads MED

8 0 23149 10200 9059 291 332 17.57 0.5 W 27653 10200 9132 317 352 12.36 1.5 S 15503 10200 8853 240 262 19.39 1.5 N 34380 10200 9473 325 353 6.925 2.5 S 30509 10200 9538 295 358 5.3512 2.5 SW 23761 10200 9161 294 353 9.2310 3 NW 18933 10200 9369 341 375 10.717 4.5 SW 19276 10200 9025 351 370 25.711 5 NW 27524 10200 9406 338 358 6.9119 5 N 16656 10200 9075 344 358 20.94 5.3 S 15755 10200 9327 292 326 6.8025 9 S 18132 10200 9205 225 250 3.5816 9.5 SW 23822 10200 9115 326 342 15.23 10 S 27600 10200 9336 332 360 18.118 10.1 NW 28537 10200 9035 340 369 17.120a 10.7 N 266 na na na na na14 14.5 SW 24107 10200 9258 301 317 18.42 15 S 33282 10200 9000 342 357 25.922 15.2 NW 34679 10200 8908 337 367 14.313 20 SW 22209 10200 9157 310 329 31.023 20.3 NW 55182 10200 9032 337 361 26.124 20.5 S 10200 10200 9365 272 297 4.681 21.5 S 24170 10200 8894 353 370 16.321 21.7 N 45407 10200 8881 357 375 13.8aIf the number of sequence reads was <10200, the site was not included in microbialcommunity analyses

APPENDIX

Table A1. Summary of sampling sites, sequence reads, and alpha diversity metrics. MED: minimum entropy decomposition, na: not applicable, OTU: operational taxonomic unit

Editorial responsibility: Pablo Sánchez Jerez, Alicante, Spain

Submitted: February 13, 2017; Accepted: July 10, 2017Proofs received from author(s): September 5, 2017