RESEARCH ARTICLE
Biogeography of planktonic and benthic cyanobacteria in coastal waters of the Big Island, Hawai’i Samuel D. Chamberlain1, Katherine A. Kaplan2, Maria Modanu3, Katherine M. Sirianni1, Senifa Annandale4 & Ian Hewson5 1
Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA; 2Department of Natural Resources, Cornell University, Ithaca, NY, USA; 3Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA; 4Natural Science Division, University of Hawai’i at Hilo, Hilo, HI, USA; and 5Department of Microbiology, Cornell University, Ithaca, NY, USA
Correspondence: Ian Hewson, Department of Microbiology, Cornell University, Ithaca, NY 14853, USA. Tel.: 607 255 0151; fax: 607 255 3904; e-mail: [email protected] Received 8 December 2013; revised 18 March 2014; accepted 25 March 2014. Final version published online 29 April 2014. DOI: 10.1111/1574-6941.12337
MICROBIOLOGY ECOLOGY
Editor: Riks Laanbroek Keywords biogeography; cyanobacteria; community; Hawaii.
Abstract Cyanobacteria are biogeochemically significant constituents of coral reef ecosystems; however, little is known about biotic and abiotic factors influencing the abundance and composition of cyanobacterial communities in fringing coral reef waters. To understand the patterns of cyanobacterial biogeography in relation to coastal environmental factors, we examined the diversity of planktonic and benthic cyanobacteria at 12 sites along the west coast of Hawaii’s Big Island. We found distinct cyanobacterial communities in sediments compared to the water column. In both sediments and water, community structure was strongly related to overall biomass (chlorophyll a concentration), although both these communities corresponded to different sets of biotic/abiotic variables. To examine the influence of freshwater input on planktonic cyanobacterial communities, we conducted a mesocosm experiment where seawater was amended with freshwater from two sources representing high- and low-human population influence. Planktonic cyanobacterial abundance decreased over time in mesocosms, although chlorophyll a concentration significantly increased with time, indicating cyanobacteria were likely outcompeted by other phytoplankton in incubations. Our results show that cyanobacterial community structure may be affected by runoff from terrestrial habitats, but that the composition of cyanobacterial communities inhabiting these locations is also structured by factors not measured in this study.
Introduction Marine cyanobacteria play a critical role in global biogeochemistry and nutrient cycling and are responsible for nearly half of global primary production (Field, 1998). Cyanobacteria produce labile organic matter (OM) through photosynthesis, which is respired as carbon dioxide by either heterotrophic bacteria or archaea (Azam & Malfatti, 2007). Cyanobacteria are therefore important to global carbon cycling and marine food webs. Most research on marine cyanobacteria in oligotrophic waters focuses on ubiquitous picocyanobacteria, for example Prochlorococcus and Synechococcus, or upon globally significant nitrogen-fixing cyanobacteria, although cyanobacteria are also an important component of coral reef ecosystems (Charpy et al., 2012) and are the dominant ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
picophytoplankton in Pacific coral reefs (Charpy, 1996, 2005; Charpy & Blanchot, 1998, 1999). In coral reefs, Synechococcus are the dominant cyanobacteria by abundance and biomass, while Prochlorococcus are dominant in adjacent open-ocean pelagic waters (Charpy & Blanchot, 1998, 1999). Coral reef cyanobacteria inhabit both benthic and planktonic habitats and play important roles in reef biogeochemistry and ecology. Benthic cyanobacterial mats are sometimes responsible for nitrogen fixation in coral reefs, supplying up to c. 25% of the nitrogen required by primary producers (Charpy-Roubaud et al., 2001; Charpy-Roubaud & Larkum, 2005; Kayanne et al., 2005; Dong et al., 2008; Charpy et al., 2009). Planktonic cyanobacteria have also been observed to fix nitrogen at ecologically significant rates in coral ecosystems (Dong et al., 2008). Cyanobacteria are also an important component of FEMS Microbiol Ecol 89 (2014) 80–88
81
Biogeography of cyanobacteria in coastal Hawaii
microbial food webs and grazed biomass in coral ecosystems (Gonzalez et al., 1998; Charpy, 2005). Reef geomorphology and hydrology influence cyanobacterial community structure, and these dynamics impact species abundance, diversity, and nutrient limitation status (Charpy & Blanchot, 1998; Dufour et al., 2001). Freshwater input to marine ecosystems influences cyanobacterial diversity and community structure (Hewson & Fuhrman, 2004; Hewson et al., 2006a). Despite a growing appreciation for the biogeochemical and ecological roles of cyanobacteria in coral reef habitats, there is little information on factors influencing their composition, especially in fringing reef ecosystems that receive substantial inputs of freshwater terrestrial runoff and groundwater discharge. One area where coral reef ecosystems experience significant terrestrial influence is the Hawaiian Island archipelago. The Hawaiian Island archipelago comprises eight major islands in the central North Pacific gyre. The islands range in age from more than 27 million years in the northwestern section of the archipelago to the most recent and growing Island of Hawaii, which contains several active and inactive volcanoes (Clague et al., 1975). As a consequence of island geology, Hawaii experiences widespread groundwater discharge, which forms submarine freshwater plumes in coastal waters (Peterson et al., 2009) and influences coastal marine ecosystems (Parsons et al., 2008). Hawaii is currently experiencing rapid human development on its drier west coast. Golf courses, beach resorts, and residential developments have been constructed to cater to a growing tourist economy (U.S. Census Bureau, 2010), although agricultural development in catchments is minimal due to extensive lava fields. Combined terrestrial runoff and groundwater discharge on Hawaii’s west coast are responsible for significant nutrient input to the coastal marine zone (Street et al., 2008). Nutrient input from terrestrial sources has been linked to human land-use and development on Hawaii’s west coast. Specifically, fertilized golf courses are responsible for significant nutrient loading to the coastal marine zone (Dollar & Atkinson, 1992; Knee et al., 2010), while less prevalent agricultural and urban land-use has not been directly linked to nutrient loading in western Hawaii (Knee et al., 2010). These inputs negatively impact coral ecosystem health (Parsons et al., 2008; Becker et al., 2013), and on the more developed island of Oahu, human-impacted terrestrial runoff has led to significant community restructuring in fringing reef ecosystems (Lapointe & Bedford, 2011). Unlike more densely populated islands, human development is diffuse along Hawaii’s western shore and pockets of undeveloped coastline still exist (Dollar & Atkinson, 1992). Due to the nature of human development on Hawaii, fringing reef ecosystems are likely receiving freshwater input of variable FEMS Microbiol Ecol 89 (2014) 80–88
quantity and quality, and the impact of freshwater inputs on Hawaiian cyanobacterial communities is not well understood. In this study, we examined the biogeography of fringing reef cyanobacterial communities in the context of several abiotic and biotic variables at 12 sites along the west coast of Hawaii. Sites were chosen to encompass a gradient of terrestrial influence, in order to examine its impacts on cyanobacterial abundance and community structure. We also examined the influence of freshwater amendment of variable quality on cyanobacterial diversity and abundance in experimental mesocosms. In both field and mesocosm studies, we quantified cyanobacterial abundance by autofluorescence microscopy and examined cyanobacterial community assemblage composition and diversity using automated ribosomal intergenic spacer analysis (ARISA). Combining experimental and observational methods enhanced our ability to understand patterns of cyanobacterial biogeography in the region and to understand the impact of terrestrial runoff and groundwater discharge on marine cyanobacterial communities.
Materials and methods Field sampling
We sampled 12 coastal sites to describe the biogeography of cyanobacterial communities and examine their response to terrestrial runoff in fringing coral reefs (Table 1). We chose our sites based on adjacent human population, freshwater input via groundwater discharge or aboveground runoff, and extent of mixing with openocean seawater. At each site (c. 2 m total water depth, which was 10–30 m offshore), we collected 4 L of surface seawater into seawater-rinsed, 2-L polycarbonate bottles. Snorkelers collected surface (0–2 cm) and deep sediments (12–14 cm) using a 60-mL syringe corer. When collecting sediments, the open syringe ends were plugged with rubber stoppers and kept vertical to ensure that no mixing occurred between surface and deep sediment profiles. Onshore, surface and deep sediments were separated and placed in sterile 50-mL tubes for storage. A YSI probe was used to measure dissolved oxygen content (mg L1), conductivity (lS cm1), salinity, temperature (°C), and pH at all sites. All samples were placed in a cooler for transport to the laboratory and processed within 4–6 h of collection. Chlorophyll a concentration
Between 0.7 and 1 L of seawater was filtered through 47mm GF/F filters (Whatman) to determine chlorophyll a ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
82
Table 1. Field site locations, salinity, temperature (°C), pH, dissolved oxygen (DO, mg L1), percentage organic matter in sediment (OM, % loss on ignition), total suspended matter (TSM, mg L1), and chlorophyll a concentration (Chl a, lg L1) Site
Lat
Long
Salinity
Temperature
pH
DO
OM
TSM
Chl a
Kiholo A Kiholo B Honaunau A Honaunau B Puako A Puako B A-Bay A A-Bay B Spencer Kohala Mahukona Pololu
19.849 19.857 19.424 19.422 19.961 19.969 19.910 19.913 20.025 20.162 20.183 20.205
155.936 155.922 155.911 155.911 155.859 155.845 155.896 155.890 155.824 155.899 155.901 155.731
33.3 32.4 32.2 29.5 30.7 31.6 32.8 28.2 28 33.1 33.1 31.8
25.4 25.3 24.6 24.9 25.4 26.2 25.5 25.2 26.1 25.7 25 24.5
8.06 7.98 7.96 7.72 7.98 8.29 7.98 8.09 8.02 8.23 8.25 8.14
8.42 8.30 8.7 11.24 9.73 19.45 19.97 26.31 8.62 15.95 11.32 8.41
1.64 0.11 1.73 0.82 2.44 5.57 3.12 8.10 4.91 1.46 2.07 NA
3.4 28.4 1.0 2.9 8.6 5.9 4.1 19.5 8.0 3.8 56.8 26.1
29.0 53.0 20.5 87.4 49.5 91.1 55.0 125.7 135.3 32.2 30.7 42.0
A-Bay, Anaehoomalu Bay.
concentration in field and mesocosm samples. Filters were folded, covered in aluminum foil, placed in whirlpaks, and frozen at 20 °C. Chlorophyll a was then analyzed according to protocols in Parsons et al. (1985), and sediment chlorophyll a was analyzed using the protocols of Hewson et al. (2001). Total suspended matter
One liter of seawater was filtered through preweighed and desiccated GF/F filters. Filters were placed in foil packets and frozen prior to analysis at Cornell University. Filters were oven-dried at 60 °C for 7 days and reweighed to quantify total suspended matter (TSM). Sediment analyses
Sediments were combusted at 525 °C for 4 h and weighed before and after combustion to determine percentage organic matter (OM) via the loss-on-ignition method (Dean, 1974). Dried sediments (c. 5 g) were sorted using a phi-scale sieve set to determine sediment size. Dried sediments were placed in sieves and shaken for 1 min, and size fractions were decanted into clean vessels. The mass of each fraction was determined by fine balance. Stable isotope analysis
All sediment and water samples were analyzed for their nitrogen stable isotope values. Anthropogenic nutrient loading into coastal waters can be identified by interpretation of nitrogen stable isotope values and has been used extensively to identify pollutant inputs to Hawaiian reefs (Parsons et al., 2008; Dailer et al., 2010; Lapointe & Bedford, 2011). d15N values were calculated relative to atmospheric nitrogen as follows: ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
d15 N ð&Þ ¼ ððRsample =Rstandard Þ 1Þ 1000; where R is the ratio of heavy to light isotopes (15N/14N) of the sample or the reference standard of atmospheric nitrogen. For seawater, 1 L of water was filtered through 47-mm GF/F filters (Whatman). Filters were folded, covered in aluminum foil, placed in whirlpaks, and frozen at 20 °C prior to isotope analysis. Sediments were milled to a fine powder on a SPEX SamplePrep Mixer/Mill. One milligram ( 0.1 mg) of each sediment and water filter was encapsulated in tin and analyzed for d15N on a Thermo Finnigan Delta V Advantage isotope ratio mass spectrometer and NC2500 elemental analyzer at Cornell University’s Stable Isotope laboratory. A laboratory standard was run for every 10 samples producing an accuracy of 0.3&. Mesocosm experiment
Freshwater input samples were collected from two locations representing variable terrestrial influence (Spencer Beach; N 20.0252, W 155.8236, and an anchialine pond located near the Anaehoomalu Resort; N 19.9089, W 155.8946), and seawater from Kiholo Bay (N 19.84899, W 155.93616). Freshwater input sources were filtered with a 0.2-lm filter to remove particulate matter. Anchialine pond freshwater was used to represent low-human population influence, and Spencer Beach runoff water was used to represent high-human population influence. Anchialine pond freshwater is similar in composition to natural groundwater inputs, whereas the freshwater collected at Spencer Beach, is influenced by a large urban/ agricultural catchment and the town of Kawaihae and flows to the ocean as aboveground runoff. Four replicate mesocosms (4-L acid-washed cubitainers) were each FEMS Microbiol Ecol 89 (2014) 80–88
83
Biogeography of cyanobacteria in coastal Hawaii
amended with 80 mL Spencer Beach water (high-impact treatment) and 80 mL anchialine pond water (low-impact treatment), and four containers served as controls (no amendment). Mesocosms were maintained at ambient light and temperature in a flow-through open-top outdoor aquarium. Mesocosms were sampled after 1, 3, 7, and 10 days of incubation, during which two replicates of each treatment were sacrificed after day 3 and the remaining two sacrificed after day 7. At each time point, two mesocosms per treatment were sampled for cyanobacterial abundance, cyanobacterial diversity, and chlorophyll a concentration. Cyanobacterial abundance
Cyanobacterial abundance was quantified by epifluorescence microscopy. Duplicate samples of seawater (10 mL) from field and mesocosm samples were diafiltered through 0.22-lm black Isopore (Millipore) filters. Filters were mounted on glass slides in 30 lL of PBS/glycerol (50% : 50%). All slides were immediately frozen prior to analysis. Autofluorescent cyanobacteria were counted under green light excitation with an Olympus BX-51 epifluorescence microscope. More than 200 autofluorescent cells were counted in 100 fields of view. Cyanobacterial community analysis
Seawater (0.7–1.0 L) was diafiltered through 0.22-lm Durapore filters (47 mm diameter), and filters were frozen in Whirl-Pak sample bags. Sediment samples were also frozen at 20 °C prior to analysis. DNA on filters was extracted using the Zymo Bacterial & Fungal DNA Mini kit, while DNA from 200 mg sediment samples was extracted using the Zymo Soil DNA Mini kit, following manufacturer’s protocols. The composition of benthic and planktonic cyanobacterial assemblages was assessed by ARISA (Fisher & Triplett, 1999) with the modifications of Hewson & Fuhrman (2004). Two microliters of extracted DNA from each sample was used as a template in PCRs. Each 50 lL reaction contained 19 PCR buffer, 2.5 mM MgCl2, 1 mM dNTPs (Promega Nucleotide Mix), 10 pmol each of primers 1392F and cyanobacterial-specific 23S-225R-TET (labeled with 50 TET fluorochrome; Rocap et al., 2002), and 0.2 ng lL1 BSA (Sigma 7030). PCR thermal cycling started with a 5-min heating step at 94 °C, followed by 30 cycles of denaturing (94 °C for 30 s), annealing (55 °C for 30 s), and extension (71 °C for 45 s), and (following thermal cycling) a final extension step at 71 °C for 7 min. PCRs were purified using Zymo Clean and Concentrator columns following manufacturer’s recommendations to remove salts and unincorporated FEMS Microbiol Ecol 89 (2014) 80–88
nucleotides and eluted in 10 lL of nuclease-free water. Purified amplified DNA was quantified using Pico Green fluorescence and diluted to 5 ng lL1. The products were then run on an ABI 377XL capillary sequencer for 4.5 h at 6 V, using a custom-made ROX-labeled size standard, which contained fragments, every 50 bp from 200 to 1500 bp (Bioventures Inc.). Outputs from fragment analysis were analyzed using the PEAK SCANNER v 1.0 program (Applied Biosystems), and then outputs on relative fluorescence intensity and size were transferred to Microsoft Excel. ARISA assemblage fingerprints were analyzed according to protocols in Hewson & Fuhrman (2006b) following the shifting bin window technique. Peaks < 0.1% of total amplified DNA fluorescence and peaks < 400 and > 1500 bp were discarded before binning 3 bp from 400 to 700 bp, 5 bp from 700 to 1000 bp, and 10 bp from 1000 to 1500 bp (Hewson & Fuhrman, 2004). Statistical analyses
For the mesocosm experiment, Tukey’s HSD analysis was used to determine significant differences between treatments within each time point, and generalized additive models (GAM) were used to determine whether response variables varied significantly with time and across treatments. The Bray–Curtis dissimilarity index was applied to ARISA assemblage fingerprints to determine pairwise differences between samples. To visualize similarities between cyanobacterial communities across sites, multiple hierarchical cluster analyses with single, complete, or average linkage were conducted on community fingerprints from all water and sediment samples. The resulting clusters were confirmed by running an analysis of similarity (ANOSIM) comparing pelagic to benthic communities. Further analyses on community structure and influences were conducted separately because water and sediment communities showed consistent differences. We examined abiotic predictor variables using pairwise linear regressions to detect collinearity and only included one of a pair of variables with Pearson correlation values of r greater than 0.9. This resulted in water cyanobacterial communities being ordinated in a canonical correspondence analysis (CCA) with seven variables (temperature, salinity, DO, chlorophyll a, pH, TSM, and d15N), while sediment communities were ordinated using nine variables (temperature, salinity, DO, chlorophyll a, pH, TSM, OM, mean sediment size, and d15N). Deep-sediment ARISA assemblage fingerprints were omitted from the sediment CCA to avoid pseudo-replication because only one set of environmental data was available for both depth profiles. CCAs were conducted in R using the ‘vegan’ ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
84
package. All statistical analyses were conducted in (R Core Team, 2013).
R
3.0.1
Results Field analyses
Mesocosm analyses
Chlorophyll a concentration varied significantly with time in mesocosm incubations (GAM, R2 = 0.697, P < 0.001), but changes in concentration were not significantly different between treatments and control. Chlorophyll a concentrations were relatively low at the beginning of all incubations (< 0.1 lg L1), peaked between days 3 and 6, and decreased to intermediate levels on day 10. On day 1, chlorophyll a concentrations in low-impact treatment were significantly higher than those of control treatments (Tukey’s HSD, P = 0.0153) and trended higher than the high-impact treatment (Tukey’s HSD, P = 0.0608). Differences between treatments became pronounced on day 3 when chlorophyll a concentration in low-impact treatment spiked to a level significantly higher than the highimpact treatment (Tukey’s HSD, P = 0.0276). On days 7 and 10, concentrations converged between treatments and decreased by day 10 (Fig. 3). Cyanobacterial abundance did not vary significantly with time or across treatment. Overall, cyanobacterial abundance decreased over time, and mean abundance dropped from between 12 300 and 15 200 cells mL1 to < 4500 cells mL1 at the end of all incubations.
W: Puako W: Mahukona W: Pololu W: Honaunau A W: Kiholo S W: Honaunau B W: A−bay A W: A−bay B W: Kiholo N W: Spencer S: Spencer Shallow S: Puako Deep B S: Puako Shallow A S: Puako Deep A S: Kohala Deep S: Puako Shallow B S: Kiholo S Shallow S: Kohala Shallow S: Kiholo N Deep S: Kiholo N Shallow S: Honaunau Shallow B S: Honaunau Deep B S: Kiholo S Deep S: Honaunau Shallow A S: Mahukona Deep S: Mahukona Shallow W: Kohala S: Honaunau Deep A W: Puako B S: A−bay Shallow B S: Spencer Deep S: A−bay Deep A S: A−bay Shallow A S: A−bay Deep B
0.8 0.4 0.0
Bray-Curtis Index
Cluster analyses revealed structuring among cyanobacterial communities, forming a distinct cluster between water and sediments (Fig. 1). This was confirmed by a significant difference between water and sediment communities (ANOSIM, R = 0.167, P = 0.001, 999 permutations). Species richness and Simpson diversity indices in sediment were significantly higher than in the water column (ANOVA, F = 3.73, P = 0.02 and F = 9.02, P < 0.001, respectively), and no differences were found in diversity indices or community structuring between shallow and deep sediments (Fig. 1). Relationships between biotic/abiotic variables and cyanobacterial community structure were visualized using CCA. The total number of cyanobacterial operational taxonomic units (OTUs; peaks in ARISA electropherograms which are approximately genera; Brown et al., 2005) present in all water samples was lower (n = 31) than in sediment samples (n = 99). In the water column, communities assembled into three broad groups, each best explained by a different combination of variables. Chlorophyll a was strongly related to OTU composition in four sites (Anaehoomalu Bay A, Anaehoomalu Bay B, Kiholo North, and Spencer Beach). OTU composition in another four sites (Pololu, Puako A, Mahukona, and Kohala) was strongly related to pH, and to a lesser degree salinity and TSM. Cyanobacterial communities at Kiholo South and Honaunau A were similar to one another, but did not correspond to measured environmental variables (Fig. 2). Cyanobacterial communities in sediment were structured in three groups, but these groupings did not match groups in the water column. One group (Kohala, Kiholo South, Puako B, and Honaunau B) was strongly associated with chlorophyll a concentrations, and d15N
displayed an equally strong, but opposing, effect. OTU composition at three sites (Mahukona, Honaunau A, and Anaehoomalu B) formed a group associated with TSM, and to a lesser degree pH, OM, and sediment size. Sites Spencer and Kiholo North formed a group primarily associated with temperature (Fig. 2). Overall, in water and sediment analyses, chlorophyll a concentration was strongly associated with cyanobacterial community composition in at least four sites. Beyond this similarity, variables exerting dominant influence differed between water and sediments. In sediments, chlorophyll a, d15N, TSM, and temperature were the strongest predictors of community structure, whereas in the water column, chlorophyll a and pH were the strongest predictors of community structure (Fig. 2).
ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
Fig. 1. Cyanobacterial community cluster using Bray–Curtis dissimilarity and complete linkage for all sediment (S) and water (W) samples. Water column samples generally cluster away from sediments, suggesting distinct cyanobacterial communities in these two environments.
FEMS Microbiol Ecol 89 (2014) 80–88
85
Sediment
2
j
1
CCA2
δ15N
TSM
h
0
pH
l e
Salinity
Temp
g
b
a
f k d
−1
OM Size
c
DO
Chl a
−3
−2
−1
0
1
2
0.8
Chlorophyll a concentration (μg L–1)
3
Biogeography of cyanobacteria in coastal Hawaii
Control High-impact Low-impact b
0.6 ab
0.4 a
0.2
a
ab
b
0.0
3
0
3
6
9
pH
DO
Chl a
TSM Temp
j ih g
0
δ15N
Salinity
a b c d e f g h i j k l
cf
−1
CCA2
1
ab l e
−2
d k
−2
−1
Water Column
0
1
2
Anaehoomalu Bay A Anaehoomalu Bay B Honaunau A Honaunau B Kiholo North Kiholo South Kohala Mahukona Pololu Puako A Puako B Spencer
3
4
CCA1 Fig. 2. CCA of sediment and water column cyanobacterial communities fitted to biotic and abiotic predictor variables. Vector length and direction indicate relative influence on community structure; letters represent weighted averages for species at each site.
Cyanobacterial abundance in the low-impact treatment increased to 43 920 2935 cells mL1 on day 3, consistent with the chlorophyll a spike observed in the lowimpact treatment on day 3 (Fig. 4). Species richness and Simpson diversity index did not vary significantly with time or across treatments in mesocosm incubations. Increases in species richness and Simpson diversity index occurred in all treatments between day 1 and 3. Increased levels of diversity were lost in control and low-impact treatments, and increased diversity was maintained in the high-impact treatment.
Discussion Bray–Curtis dissimilarity indices suggest that compositionally distinct cyanobacterial communities exist between the water column and sediments (Fig. 1). Differences in bacterial community composition between the water FEMS Microbiol Ecol 89 (2014) 80–88
Fig. 3. Chlorophyll a concentration (lg L1) at different sampling time points in mesocosm treatments. High-impact treatment was amended with freshwater from Spencer Beach, low-impact treatment was amended with freshwater from an anchialine pool, and control received no freshwater addition. Letters indicate significant differences within each time point determined by Tukey’s HSD (P < 0.05). Means and standard error are presented for each time point (n = 2).
Cyanobacterial abundance (cells mL–1)
2
Time (Days)
Control High-impact Low-impact
40 000
30 000
20 000
10 000
0
0
3
6
9
Time (Days) Fig. 4. Cyanobacterial abundance (cells mL1) at different sampling time points in mesocosm treatments. High-impact treatment was amended with freshwater from Spencer Beach, low-impact treatment was amended with freshwater from an anchialine pool, and control received no freshwater addition. Means and standard error are presented for each time point (n = 2).
column and sediments have been previously observed in marine ecosystems (Stevens et al., 2005; Hewson & Fuhrman, 2006a; Lozupone & Knight, 2007). These observations were further supported by CCAs, which show clear differences in water column and sediment community structure (Fig. 2). Increased species richness and diversity ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
86
were found in sediments, which follows previous observations of high levels of microbial diversity in sediment ecosystems (Lozupone & Knight, 2007). Distinct communities were not observed between surface (0–2 cm) and deep (12–14 cm) sediment profiles (Fig. 1), although community structuring between surface and deep sediments is a feature observed in other marine and reef environments (Hewson & Fuhrman, 2006a; Hewson et al., 2007). Here, a lack of community structure between sediment profiles potentially indicates homogenization between surface and deep sediment profiles. This is likely due to mixing between these profiles, as sediments were collected in c. 2 m of water in areas of high surf and tidal action. Bioturbation by burrowing organisms may have caused homogenization of deep and shallow sediment horizons. Based on our observations, cyanobacterial community composition corresponds most strongly with overall biomass (inferred from chlorophyll a concentration) and less strongly with other measured environmental parameters. CCA results also indicate that sediment and water column communities may respond differently to biotic/abiotic variables and environmental conditions. In sediments, chlorophyll a, d15N, TSM, and temperature were the strongest predictors of community structure, while in the water column, chlorophyll a and pH were the strongest predictors of community structure (Fig. 2). The correspondence of d15N and TSM to sediment OTUs may indicate the influence of anthropogenic nutrient loading on sediment cyanobacterial communities. Chlorophyll a concentration (overall biomass) was the strongest predictor of community composition in both sediment and water column, and it corresponded strongly to unique community assemblages in both environments (Fig. 2). Productive nearshore environments may favor particular community assemblages of cyanobacteria that are not dominant in oligotrophic marine systems. This may reflect the transition between oligotrophic openocean cyanobacterial communities and those more typical of mesotrophic coastal conditions present in fringing coral reef habitats. These results are in line with the general observation of transitions from Prochlorococcus-dominant open-ocean waters to Synechococcus-dominant coral reef ecosystems (Charpy & Blanchot, 1998, 1999) and other observations of distinct cyanobacterial community structuring at the freshwater–seawater interface (Hewson et al., 2006a, 2007). Bacterial community richness and diversity have been shown to increase with productivity in a number of marine ecosystems (Horner-Devine et al., 2004; Hewson et al., 2006a, b, 2007; Hewson & Fuhrman, 2007). Our mesocosm results indicate that as water column chlorophyll a concentration and overall biomass increase ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
(Fig. 3), cyanobacterial abundance decreases (Fig. 4). It is therefore likely that other phytoplankton outcompete cyanobacteria in experimental mesocosms. Variable response between treatments indicates that input from sources of variable quality may have differential effects on reef cyanobacterial communities. Specifically, we observed a large spike in cyanobacterial abundance on day 3 of the low-impact freshwater-amended treatment (Fig. 4), although in all treatments cyanobacterial abundance decreased to similar levels by the end of incubation. Extending our results to coastal phytoplankton, it is possible that when a coastal zone receives an initial pulse of groundwater discharge, cyanobacterial populations will increase, but over longer periods or with chronic loading, more competitive phytoplankton populations replace cyanobacteria. The similar response of cyanobacteria to both inputs suggests a general response of marine cyanobacteria to coastal freshwater input. Comparison of mesocosm observation with water column CCA shows that while community structuring is primarily related to chlorophyll a concentration and productivity (Fig. 2), a particular water column cyanobacterial community assemblage may be favored in coastal systems where cyanobacteria are outcompeted by eukaryotic phytoplankton. These observations support the idea that oligotrophic open-ocean cyanobacterial communities may be replaced by unique communities when in contact with coastal zones of groundwater discharge, such as Hawaii’s west coast. Our results suggest that cyanobacterial communities in the water column and sediments of the fringing coral reef are distinct and that their community structure is related to the overall biomass and productivity of their ecosystems. However, our results also highlight strong site-specific heterogeneity in composition that is related to localized abiotic and biotic factors. Benthic and planktonic cyanobacterial communities correspond to separate sets of environmental variables, and as a result, these communities likely respond differentially to environmental change. Furthermore, our results provide evidence that terrestrial inputs may cause changes to the composition and abundance of cyanobacterial communities, leading to communities that are distinct from open-ocean ecosystems. Hence, as expected, increased human development in catchments that influence freshwater discharge into coastal zones (Dollar & Atkinson, 1992; Knee et al., 2010) may restructure pelagic, oligotrophic cyanobacterial communities advected from the open ocean. Moreover, our results suggest that cyanobacteria inhabiting the fringing reefs of Hawaii are sensitive to freshwater inputs, and planktonic and benthic cyanobacterial communities may exhibit distinct community responses to environmental change. FEMS Microbiol Ecol 89 (2014) 80–88
Biogeography of cyanobacteria in coastal Hawaii
Acknowledgements We thank the Department of Ecology and Evolutionary Biology at Cornell University for funding and support. The authors thank N. Hairston, J. Sparks, and the students of Cornell Graduate Tropical Field Ecology, January 2013, for assistance with sample collection, transport, and processing. This work was supported by NSF grant OCE 0961894 awarded to IH.
References Azam F & Malfatti F (2007) Microbial structuring of marine ecosystems. Nat Rev Microbiol 5: 782–791. Brown MV, Schwalbach MS, Hewson I & Fuhrman JA (2005) Coupling 16S-ITS rDNA clone libraries and ARISA to show marine microbial diversity: development and application to a time series. Environ Microbiol 7: 1466–1479. Bureau UC (2010) Statewide Population Growth Rates. Hawai’i State Department of Business, Economic Development & Tourism, Suitland, MD, USA. Charpy L (1996) Phytoplankton biomass and production in two Tuamotu atoll lagoons (French Polynesia). Mar Ecol Prog Ser 145: 133–142. Charpy L (2005) Importance of photosynthetic picoplankton in coral reef ecosystems. Vie Milieu 55: 217–224. Charpy L & Blanchot J (1998) Photosynthetic picoplankton in French Polynesian atoll lagoons: estimation of taxa contribution to biomass and production by flow cytometry. Mar Ecol Prog Ser 162: 57–70. Charpy L & Blanchot J (1999) Picophytoplankton biomass, community structure and productivity in the Great Astrolabe Lagoon, Fiji. Coral Reefs 18: 255–262. Charpy L, Palinska KA, Casareto B, Langlade MJ, Suzuki Y, Abed RMM & Golubic S (2009) Dinitrogen-fixing cyanobacteria in microbial mats of two shallow coral reef ecosystems. Microb Ecol 59: 174–186. Charpy L, Casareto BE, Langlade MJ & Suzuki Y (2012) Cyanobacteria in coral reef ecosystems: a review. J Mar Biol 2012: 1–9. Charpy-Roubaud C & Larkum AWD (2005) Dinitrogen fixation by exposed communities on the rim of Tikehau atoll (Tuamotu Archipelago, French Polynesia). Coral Reefs 24: 622–628. Charpy-Roubaud C, Charpy L & Larkum A (2001) Atmospheric dinitrogen fixation by benthic communities of Tikehau Lagoon (Tuamotu Archipelago, French Polynesia) and its contribution to benthic primary production. Mar Biol 139: 991–998. Clague DA, Dalrymple GB & Moberly R (1975) Petrography and K-Ar ages of dredged volcanic rocks from the western Hawaiian Ridge and the southern Emperor Seamount chain. Geol Soc Am Bull 86: 991–998. Dailer ML, Knox RS, Smith JE, Napier M & Smith CM (2010) Using d15N values in algal tissue to map locations and
FEMS Microbiol Ecol 89 (2014) 80–88
87
potential sources of anthropogenic nutrient inputs on the island of Maui, Hawai’i, USA. Mar Pollut Bull 60: 655–671. Dean WE (1974) Determination of carbonate and organic matter in calcareous sediments and sedimentary rocks by loss on ignition; comparison with other methods. J Sediment Res 44: 242–248. Dollar SJ & Atkinson MJ (1992) Effects of nutrient subsidies from groundwater to nearshore marine ecosystems off the island of Hawaii. Estuar Coast Shelf Sci 35: 409–424. Dong J, Zhang Y, Wang Y, Zhang S & Wang H (2008) Spatial and seasonal variations of cyanobacteria and their nitrogen fixation rates in Sanya Bay, South China Sea. Sci Mar 72: 239–251. Dufour P, Andrefou€et S, Charpy L & Garcia N (2001) Atoll morphometry controls lagoon nutrient regime. Limnol Oceanogr 46: 456–461. Field CB (1998) Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281: 237–240. Fisher MM & Triplett EW (1999) Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities. Appl Environ Microbiol 65: 4630–4636. Gonzalez JM, Torreton J-P, Dufour P & Charpy L (1998) Temporal and spatial dynamics of the pelagic microbial food web in an atoll lagoon. Aquat Microb Ecol 16: 53–64. Guilherme Becker C, Dalziel BD, Kersch Becker MF, Park MG & Mouchka M (2013) Indirect effects of human development along the coast on coral health. Biotropica 45: 401–407. Hewson I & Fuhrman JA (2004) Richness and diversity of bacterioplankton species along an estuarine gradient in Moreton Bay, Australia. Appl Environ Microbiol 70: 3425– 3433. Hewson I & Fuhrman JA (2006a) Spatial and vertical biogeography of coral reef sediment bacterial and diazotroph communities. Mar Ecol Prog Ser 306: 79–86. Hewson I & Fuhrman JA (2006b) Viral impacts upon marine bacterioplankton assemblage structure. J Mar Biol Assoc UK 86: 577–589. Hewson I & Fuhrman JA (2007) Covariation of viral parameters with bacterial assemblage richness and diversity in the water column and sediments. Deep Sea Res Part I 54: 811–830. Hewson I, O’Neil JM, Fuhrman JA & Dennison WC (2001) Virus-like particle distribution and abundance in sediments and overlying waters along eutrophication gradients in two subtropical estuaries. Limnol Oceanogr 46: 1734–1746. Hewson I, Capone DG, Steele JA & Fuhrman JA (2006a) Influence of Amazon and Orinoco offshore surface water plumes on oligotrophic bacterioplankton diversity in the west tropical Atlantic. Aquat Microb Ecol 43: 11–22. Hewson I, Steele JA, Capone DG & Fuhrman JA (2006b) Remarkable heterogeneity in meso- and bathypelagic bacterioplankton assemblage composition. Limnol Oceanogr 51: 1274–1283.
ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
88
Hewson I, Jacobson Meyers ME & Fuhrman JA (2007) Diversity and biogeography of bacterial assemblages in surface sediments across the San Pedro Basin, Southern California Borderlands. Environ Microbiol 9: 923–933. Horner-Devine MC, Carney KM & Bohannan BJM (2004) An ecological perspective on bacterial biodiversity. Proc R Soc Lond B Biol Sci 271: 113–122. Kayanne H, Hirota M, Yamamuro M & Koike I (2005) Nitrogen fixation of filamentous cyanobacteria in a coral reef measured using three different methods. Coral Reefs 24: 197–200. Knee K, Street JH, Grossman EG & Paytan A (2010) Nutrient inputs to the coastal ocean from submarine groundwater discharge in a groundwater-dominated system: relation to land use (Kona coast, Hawaii, U.S.A.). Limnol Oceanogr 55: 1105–1122. Lapointe BE & Bedford BJ (2011) Stormwater nutrient inputs favor growth of non-native macroalgae (Rhodophyta) on O’ahu, Hawaiian Islands. Harmful Algae 10: 310–318. Lozupone CA & Knight R (2007) Global patterns in bacterial diversity. P Natl Acad Sci USA 104: 11436–11440. Parsons TR, Maita Y & Lalli CM (1985) A Manual of Chemical and Biological Methods for Seawater Analysis. Pergamon Press, Oxford.
ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
Parsons ML, Walsh WJ, Settlemier CJ, White DJ, Ballauer JM, Ayotte PM, Osada KM & Carman B (2008) A multivariate assessment of the coral ecosystem health of two embayments on the lee of the island of Hawai’i. Mar Pollut Bull 56: 1138–1149. Peterson RN, Burnett WC, Glenn CR & Johnson A (2009) Quantification of point-source groundwater discharges to the ocean from the shoreline of the Big Island, Hawaii. Limnol Oceanogr 54: 890–904. R Core Team (2013) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Rocap G, Distel DL, Waterbury JB & Chisholm SW (2002) Resolution of Prochlorococcus and Synechococcus ecotypes by using 16S–23S ribosomal DNA internal transcribed spacer sequences. Appl Environ Microbiol 68: 1180–1191. Stevens H, Brinkhoff T & Simon M (2005) Composition of free-living, aggregate-associated and sediment surface-associated bacterial communities in the German Wadden Sea. Aquat Microb Ecol 38: 15–30. Street JH, Knee KL, Grossman EE & Paytan A (2008) Submarine groundwater discharge and nutrient addition to the coastal zone and coral reefs of leeward Hawai’i. Mar Chem 109: 355–376.
FEMS Microbiol Ecol 89 (2014) 80–88
Biogeography of planktonic and benthic cyanobacteria in coastal waters of the Big Island, Hawai’i Samuel D. Chamberlain1, Katherine A. Kaplan2, Maria Modanu3, Katherine M. Sirianni1, Senifa Annandale4 & Ian Hewson5 1
Department of Ecology and Evolutionary Biology, Cornell University, Ithaca, NY, USA; 2Department of Natural Resources, Cornell University, Ithaca, NY, USA; 3Department of Neurobiology and Behavior, Cornell University, Ithaca, NY, USA; 4Natural Science Division, University of Hawai’i at Hilo, Hilo, HI, USA; and 5Department of Microbiology, Cornell University, Ithaca, NY, USA
Correspondence: Ian Hewson, Department of Microbiology, Cornell University, Ithaca, NY 14853, USA. Tel.: 607 255 0151; fax: 607 255 3904; e-mail: [email protected] Received 8 December 2013; revised 18 March 2014; accepted 25 March 2014. Final version published online 29 April 2014. DOI: 10.1111/1574-6941.12337
MICROBIOLOGY ECOLOGY
Editor: Riks Laanbroek Keywords biogeography; cyanobacteria; community; Hawaii.
Abstract Cyanobacteria are biogeochemically significant constituents of coral reef ecosystems; however, little is known about biotic and abiotic factors influencing the abundance and composition of cyanobacterial communities in fringing coral reef waters. To understand the patterns of cyanobacterial biogeography in relation to coastal environmental factors, we examined the diversity of planktonic and benthic cyanobacteria at 12 sites along the west coast of Hawaii’s Big Island. We found distinct cyanobacterial communities in sediments compared to the water column. In both sediments and water, community structure was strongly related to overall biomass (chlorophyll a concentration), although both these communities corresponded to different sets of biotic/abiotic variables. To examine the influence of freshwater input on planktonic cyanobacterial communities, we conducted a mesocosm experiment where seawater was amended with freshwater from two sources representing high- and low-human population influence. Planktonic cyanobacterial abundance decreased over time in mesocosms, although chlorophyll a concentration significantly increased with time, indicating cyanobacteria were likely outcompeted by other phytoplankton in incubations. Our results show that cyanobacterial community structure may be affected by runoff from terrestrial habitats, but that the composition of cyanobacterial communities inhabiting these locations is also structured by factors not measured in this study.
Introduction Marine cyanobacteria play a critical role in global biogeochemistry and nutrient cycling and are responsible for nearly half of global primary production (Field, 1998). Cyanobacteria produce labile organic matter (OM) through photosynthesis, which is respired as carbon dioxide by either heterotrophic bacteria or archaea (Azam & Malfatti, 2007). Cyanobacteria are therefore important to global carbon cycling and marine food webs. Most research on marine cyanobacteria in oligotrophic waters focuses on ubiquitous picocyanobacteria, for example Prochlorococcus and Synechococcus, or upon globally significant nitrogen-fixing cyanobacteria, although cyanobacteria are also an important component of coral reef ecosystems (Charpy et al., 2012) and are the dominant ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
picophytoplankton in Pacific coral reefs (Charpy, 1996, 2005; Charpy & Blanchot, 1998, 1999). In coral reefs, Synechococcus are the dominant cyanobacteria by abundance and biomass, while Prochlorococcus are dominant in adjacent open-ocean pelagic waters (Charpy & Blanchot, 1998, 1999). Coral reef cyanobacteria inhabit both benthic and planktonic habitats and play important roles in reef biogeochemistry and ecology. Benthic cyanobacterial mats are sometimes responsible for nitrogen fixation in coral reefs, supplying up to c. 25% of the nitrogen required by primary producers (Charpy-Roubaud et al., 2001; Charpy-Roubaud & Larkum, 2005; Kayanne et al., 2005; Dong et al., 2008; Charpy et al., 2009). Planktonic cyanobacteria have also been observed to fix nitrogen at ecologically significant rates in coral ecosystems (Dong et al., 2008). Cyanobacteria are also an important component of FEMS Microbiol Ecol 89 (2014) 80–88
81
Biogeography of cyanobacteria in coastal Hawaii
microbial food webs and grazed biomass in coral ecosystems (Gonzalez et al., 1998; Charpy, 2005). Reef geomorphology and hydrology influence cyanobacterial community structure, and these dynamics impact species abundance, diversity, and nutrient limitation status (Charpy & Blanchot, 1998; Dufour et al., 2001). Freshwater input to marine ecosystems influences cyanobacterial diversity and community structure (Hewson & Fuhrman, 2004; Hewson et al., 2006a). Despite a growing appreciation for the biogeochemical and ecological roles of cyanobacteria in coral reef habitats, there is little information on factors influencing their composition, especially in fringing reef ecosystems that receive substantial inputs of freshwater terrestrial runoff and groundwater discharge. One area where coral reef ecosystems experience significant terrestrial influence is the Hawaiian Island archipelago. The Hawaiian Island archipelago comprises eight major islands in the central North Pacific gyre. The islands range in age from more than 27 million years in the northwestern section of the archipelago to the most recent and growing Island of Hawaii, which contains several active and inactive volcanoes (Clague et al., 1975). As a consequence of island geology, Hawaii experiences widespread groundwater discharge, which forms submarine freshwater plumes in coastal waters (Peterson et al., 2009) and influences coastal marine ecosystems (Parsons et al., 2008). Hawaii is currently experiencing rapid human development on its drier west coast. Golf courses, beach resorts, and residential developments have been constructed to cater to a growing tourist economy (U.S. Census Bureau, 2010), although agricultural development in catchments is minimal due to extensive lava fields. Combined terrestrial runoff and groundwater discharge on Hawaii’s west coast are responsible for significant nutrient input to the coastal marine zone (Street et al., 2008). Nutrient input from terrestrial sources has been linked to human land-use and development on Hawaii’s west coast. Specifically, fertilized golf courses are responsible for significant nutrient loading to the coastal marine zone (Dollar & Atkinson, 1992; Knee et al., 2010), while less prevalent agricultural and urban land-use has not been directly linked to nutrient loading in western Hawaii (Knee et al., 2010). These inputs negatively impact coral ecosystem health (Parsons et al., 2008; Becker et al., 2013), and on the more developed island of Oahu, human-impacted terrestrial runoff has led to significant community restructuring in fringing reef ecosystems (Lapointe & Bedford, 2011). Unlike more densely populated islands, human development is diffuse along Hawaii’s western shore and pockets of undeveloped coastline still exist (Dollar & Atkinson, 1992). Due to the nature of human development on Hawaii, fringing reef ecosystems are likely receiving freshwater input of variable FEMS Microbiol Ecol 89 (2014) 80–88
quantity and quality, and the impact of freshwater inputs on Hawaiian cyanobacterial communities is not well understood. In this study, we examined the biogeography of fringing reef cyanobacterial communities in the context of several abiotic and biotic variables at 12 sites along the west coast of Hawaii. Sites were chosen to encompass a gradient of terrestrial influence, in order to examine its impacts on cyanobacterial abundance and community structure. We also examined the influence of freshwater amendment of variable quality on cyanobacterial diversity and abundance in experimental mesocosms. In both field and mesocosm studies, we quantified cyanobacterial abundance by autofluorescence microscopy and examined cyanobacterial community assemblage composition and diversity using automated ribosomal intergenic spacer analysis (ARISA). Combining experimental and observational methods enhanced our ability to understand patterns of cyanobacterial biogeography in the region and to understand the impact of terrestrial runoff and groundwater discharge on marine cyanobacterial communities.
Materials and methods Field sampling
We sampled 12 coastal sites to describe the biogeography of cyanobacterial communities and examine their response to terrestrial runoff in fringing coral reefs (Table 1). We chose our sites based on adjacent human population, freshwater input via groundwater discharge or aboveground runoff, and extent of mixing with openocean seawater. At each site (c. 2 m total water depth, which was 10–30 m offshore), we collected 4 L of surface seawater into seawater-rinsed, 2-L polycarbonate bottles. Snorkelers collected surface (0–2 cm) and deep sediments (12–14 cm) using a 60-mL syringe corer. When collecting sediments, the open syringe ends were plugged with rubber stoppers and kept vertical to ensure that no mixing occurred between surface and deep sediment profiles. Onshore, surface and deep sediments were separated and placed in sterile 50-mL tubes for storage. A YSI probe was used to measure dissolved oxygen content (mg L1), conductivity (lS cm1), salinity, temperature (°C), and pH at all sites. All samples were placed in a cooler for transport to the laboratory and processed within 4–6 h of collection. Chlorophyll a concentration
Between 0.7 and 1 L of seawater was filtered through 47mm GF/F filters (Whatman) to determine chlorophyll a ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
82
Table 1. Field site locations, salinity, temperature (°C), pH, dissolved oxygen (DO, mg L1), percentage organic matter in sediment (OM, % loss on ignition), total suspended matter (TSM, mg L1), and chlorophyll a concentration (Chl a, lg L1) Site
Lat
Long
Salinity
Temperature
pH
DO
OM
TSM
Chl a
Kiholo A Kiholo B Honaunau A Honaunau B Puako A Puako B A-Bay A A-Bay B Spencer Kohala Mahukona Pololu
19.849 19.857 19.424 19.422 19.961 19.969 19.910 19.913 20.025 20.162 20.183 20.205
155.936 155.922 155.911 155.911 155.859 155.845 155.896 155.890 155.824 155.899 155.901 155.731
33.3 32.4 32.2 29.5 30.7 31.6 32.8 28.2 28 33.1 33.1 31.8
25.4 25.3 24.6 24.9 25.4 26.2 25.5 25.2 26.1 25.7 25 24.5
8.06 7.98 7.96 7.72 7.98 8.29 7.98 8.09 8.02 8.23 8.25 8.14
8.42 8.30 8.7 11.24 9.73 19.45 19.97 26.31 8.62 15.95 11.32 8.41
1.64 0.11 1.73 0.82 2.44 5.57 3.12 8.10 4.91 1.46 2.07 NA
3.4 28.4 1.0 2.9 8.6 5.9 4.1 19.5 8.0 3.8 56.8 26.1
29.0 53.0 20.5 87.4 49.5 91.1 55.0 125.7 135.3 32.2 30.7 42.0
A-Bay, Anaehoomalu Bay.
concentration in field and mesocosm samples. Filters were folded, covered in aluminum foil, placed in whirlpaks, and frozen at 20 °C. Chlorophyll a was then analyzed according to protocols in Parsons et al. (1985), and sediment chlorophyll a was analyzed using the protocols of Hewson et al. (2001). Total suspended matter
One liter of seawater was filtered through preweighed and desiccated GF/F filters. Filters were placed in foil packets and frozen prior to analysis at Cornell University. Filters were oven-dried at 60 °C for 7 days and reweighed to quantify total suspended matter (TSM). Sediment analyses
Sediments were combusted at 525 °C for 4 h and weighed before and after combustion to determine percentage organic matter (OM) via the loss-on-ignition method (Dean, 1974). Dried sediments (c. 5 g) were sorted using a phi-scale sieve set to determine sediment size. Dried sediments were placed in sieves and shaken for 1 min, and size fractions were decanted into clean vessels. The mass of each fraction was determined by fine balance. Stable isotope analysis
All sediment and water samples were analyzed for their nitrogen stable isotope values. Anthropogenic nutrient loading into coastal waters can be identified by interpretation of nitrogen stable isotope values and has been used extensively to identify pollutant inputs to Hawaiian reefs (Parsons et al., 2008; Dailer et al., 2010; Lapointe & Bedford, 2011). d15N values were calculated relative to atmospheric nitrogen as follows: ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
d15 N ð&Þ ¼ ððRsample =Rstandard Þ 1Þ 1000; where R is the ratio of heavy to light isotopes (15N/14N) of the sample or the reference standard of atmospheric nitrogen. For seawater, 1 L of water was filtered through 47-mm GF/F filters (Whatman). Filters were folded, covered in aluminum foil, placed in whirlpaks, and frozen at 20 °C prior to isotope analysis. Sediments were milled to a fine powder on a SPEX SamplePrep Mixer/Mill. One milligram ( 0.1 mg) of each sediment and water filter was encapsulated in tin and analyzed for d15N on a Thermo Finnigan Delta V Advantage isotope ratio mass spectrometer and NC2500 elemental analyzer at Cornell University’s Stable Isotope laboratory. A laboratory standard was run for every 10 samples producing an accuracy of 0.3&. Mesocosm experiment
Freshwater input samples were collected from two locations representing variable terrestrial influence (Spencer Beach; N 20.0252, W 155.8236, and an anchialine pond located near the Anaehoomalu Resort; N 19.9089, W 155.8946), and seawater from Kiholo Bay (N 19.84899, W 155.93616). Freshwater input sources were filtered with a 0.2-lm filter to remove particulate matter. Anchialine pond freshwater was used to represent low-human population influence, and Spencer Beach runoff water was used to represent high-human population influence. Anchialine pond freshwater is similar in composition to natural groundwater inputs, whereas the freshwater collected at Spencer Beach, is influenced by a large urban/ agricultural catchment and the town of Kawaihae and flows to the ocean as aboveground runoff. Four replicate mesocosms (4-L acid-washed cubitainers) were each FEMS Microbiol Ecol 89 (2014) 80–88
83
Biogeography of cyanobacteria in coastal Hawaii
amended with 80 mL Spencer Beach water (high-impact treatment) and 80 mL anchialine pond water (low-impact treatment), and four containers served as controls (no amendment). Mesocosms were maintained at ambient light and temperature in a flow-through open-top outdoor aquarium. Mesocosms were sampled after 1, 3, 7, and 10 days of incubation, during which two replicates of each treatment were sacrificed after day 3 and the remaining two sacrificed after day 7. At each time point, two mesocosms per treatment were sampled for cyanobacterial abundance, cyanobacterial diversity, and chlorophyll a concentration. Cyanobacterial abundance
Cyanobacterial abundance was quantified by epifluorescence microscopy. Duplicate samples of seawater (10 mL) from field and mesocosm samples were diafiltered through 0.22-lm black Isopore (Millipore) filters. Filters were mounted on glass slides in 30 lL of PBS/glycerol (50% : 50%). All slides were immediately frozen prior to analysis. Autofluorescent cyanobacteria were counted under green light excitation with an Olympus BX-51 epifluorescence microscope. More than 200 autofluorescent cells were counted in 100 fields of view. Cyanobacterial community analysis
Seawater (0.7–1.0 L) was diafiltered through 0.22-lm Durapore filters (47 mm diameter), and filters were frozen in Whirl-Pak sample bags. Sediment samples were also frozen at 20 °C prior to analysis. DNA on filters was extracted using the Zymo Bacterial & Fungal DNA Mini kit, while DNA from 200 mg sediment samples was extracted using the Zymo Soil DNA Mini kit, following manufacturer’s protocols. The composition of benthic and planktonic cyanobacterial assemblages was assessed by ARISA (Fisher & Triplett, 1999) with the modifications of Hewson & Fuhrman (2004). Two microliters of extracted DNA from each sample was used as a template in PCRs. Each 50 lL reaction contained 19 PCR buffer, 2.5 mM MgCl2, 1 mM dNTPs (Promega Nucleotide Mix), 10 pmol each of primers 1392F and cyanobacterial-specific 23S-225R-TET (labeled with 50 TET fluorochrome; Rocap et al., 2002), and 0.2 ng lL1 BSA (Sigma 7030). PCR thermal cycling started with a 5-min heating step at 94 °C, followed by 30 cycles of denaturing (94 °C for 30 s), annealing (55 °C for 30 s), and extension (71 °C for 45 s), and (following thermal cycling) a final extension step at 71 °C for 7 min. PCRs were purified using Zymo Clean and Concentrator columns following manufacturer’s recommendations to remove salts and unincorporated FEMS Microbiol Ecol 89 (2014) 80–88
nucleotides and eluted in 10 lL of nuclease-free water. Purified amplified DNA was quantified using Pico Green fluorescence and diluted to 5 ng lL1. The products were then run on an ABI 377XL capillary sequencer for 4.5 h at 6 V, using a custom-made ROX-labeled size standard, which contained fragments, every 50 bp from 200 to 1500 bp (Bioventures Inc.). Outputs from fragment analysis were analyzed using the PEAK SCANNER v 1.0 program (Applied Biosystems), and then outputs on relative fluorescence intensity and size were transferred to Microsoft Excel. ARISA assemblage fingerprints were analyzed according to protocols in Hewson & Fuhrman (2006b) following the shifting bin window technique. Peaks < 0.1% of total amplified DNA fluorescence and peaks < 400 and > 1500 bp were discarded before binning 3 bp from 400 to 700 bp, 5 bp from 700 to 1000 bp, and 10 bp from 1000 to 1500 bp (Hewson & Fuhrman, 2004). Statistical analyses
For the mesocosm experiment, Tukey’s HSD analysis was used to determine significant differences between treatments within each time point, and generalized additive models (GAM) were used to determine whether response variables varied significantly with time and across treatments. The Bray–Curtis dissimilarity index was applied to ARISA assemblage fingerprints to determine pairwise differences between samples. To visualize similarities between cyanobacterial communities across sites, multiple hierarchical cluster analyses with single, complete, or average linkage were conducted on community fingerprints from all water and sediment samples. The resulting clusters were confirmed by running an analysis of similarity (ANOSIM) comparing pelagic to benthic communities. Further analyses on community structure and influences were conducted separately because water and sediment communities showed consistent differences. We examined abiotic predictor variables using pairwise linear regressions to detect collinearity and only included one of a pair of variables with Pearson correlation values of r greater than 0.9. This resulted in water cyanobacterial communities being ordinated in a canonical correspondence analysis (CCA) with seven variables (temperature, salinity, DO, chlorophyll a, pH, TSM, and d15N), while sediment communities were ordinated using nine variables (temperature, salinity, DO, chlorophyll a, pH, TSM, OM, mean sediment size, and d15N). Deep-sediment ARISA assemblage fingerprints were omitted from the sediment CCA to avoid pseudo-replication because only one set of environmental data was available for both depth profiles. CCAs were conducted in R using the ‘vegan’ ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
84
package. All statistical analyses were conducted in (R Core Team, 2013).
R
3.0.1
Results Field analyses
Mesocosm analyses
Chlorophyll a concentration varied significantly with time in mesocosm incubations (GAM, R2 = 0.697, P < 0.001), but changes in concentration were not significantly different between treatments and control. Chlorophyll a concentrations were relatively low at the beginning of all incubations (< 0.1 lg L1), peaked between days 3 and 6, and decreased to intermediate levels on day 10. On day 1, chlorophyll a concentrations in low-impact treatment were significantly higher than those of control treatments (Tukey’s HSD, P = 0.0153) and trended higher than the high-impact treatment (Tukey’s HSD, P = 0.0608). Differences between treatments became pronounced on day 3 when chlorophyll a concentration in low-impact treatment spiked to a level significantly higher than the highimpact treatment (Tukey’s HSD, P = 0.0276). On days 7 and 10, concentrations converged between treatments and decreased by day 10 (Fig. 3). Cyanobacterial abundance did not vary significantly with time or across treatment. Overall, cyanobacterial abundance decreased over time, and mean abundance dropped from between 12 300 and 15 200 cells mL1 to < 4500 cells mL1 at the end of all incubations.
W: Puako W: Mahukona W: Pololu W: Honaunau A W: Kiholo S W: Honaunau B W: A−bay A W: A−bay B W: Kiholo N W: Spencer S: Spencer Shallow S: Puako Deep B S: Puako Shallow A S: Puako Deep A S: Kohala Deep S: Puako Shallow B S: Kiholo S Shallow S: Kohala Shallow S: Kiholo N Deep S: Kiholo N Shallow S: Honaunau Shallow B S: Honaunau Deep B S: Kiholo S Deep S: Honaunau Shallow A S: Mahukona Deep S: Mahukona Shallow W: Kohala S: Honaunau Deep A W: Puako B S: A−bay Shallow B S: Spencer Deep S: A−bay Deep A S: A−bay Shallow A S: A−bay Deep B
0.8 0.4 0.0
Bray-Curtis Index
Cluster analyses revealed structuring among cyanobacterial communities, forming a distinct cluster between water and sediments (Fig. 1). This was confirmed by a significant difference between water and sediment communities (ANOSIM, R = 0.167, P = 0.001, 999 permutations). Species richness and Simpson diversity indices in sediment were significantly higher than in the water column (ANOVA, F = 3.73, P = 0.02 and F = 9.02, P < 0.001, respectively), and no differences were found in diversity indices or community structuring between shallow and deep sediments (Fig. 1). Relationships between biotic/abiotic variables and cyanobacterial community structure were visualized using CCA. The total number of cyanobacterial operational taxonomic units (OTUs; peaks in ARISA electropherograms which are approximately genera; Brown et al., 2005) present in all water samples was lower (n = 31) than in sediment samples (n = 99). In the water column, communities assembled into three broad groups, each best explained by a different combination of variables. Chlorophyll a was strongly related to OTU composition in four sites (Anaehoomalu Bay A, Anaehoomalu Bay B, Kiholo North, and Spencer Beach). OTU composition in another four sites (Pololu, Puako A, Mahukona, and Kohala) was strongly related to pH, and to a lesser degree salinity and TSM. Cyanobacterial communities at Kiholo South and Honaunau A were similar to one another, but did not correspond to measured environmental variables (Fig. 2). Cyanobacterial communities in sediment were structured in three groups, but these groupings did not match groups in the water column. One group (Kohala, Kiholo South, Puako B, and Honaunau B) was strongly associated with chlorophyll a concentrations, and d15N
displayed an equally strong, but opposing, effect. OTU composition at three sites (Mahukona, Honaunau A, and Anaehoomalu B) formed a group associated with TSM, and to a lesser degree pH, OM, and sediment size. Sites Spencer and Kiholo North formed a group primarily associated with temperature (Fig. 2). Overall, in water and sediment analyses, chlorophyll a concentration was strongly associated with cyanobacterial community composition in at least four sites. Beyond this similarity, variables exerting dominant influence differed between water and sediments. In sediments, chlorophyll a, d15N, TSM, and temperature were the strongest predictors of community structure, whereas in the water column, chlorophyll a and pH were the strongest predictors of community structure (Fig. 2).
ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
Fig. 1. Cyanobacterial community cluster using Bray–Curtis dissimilarity and complete linkage for all sediment (S) and water (W) samples. Water column samples generally cluster away from sediments, suggesting distinct cyanobacterial communities in these two environments.
FEMS Microbiol Ecol 89 (2014) 80–88
85
Sediment
2
j
1
CCA2
δ15N
TSM
h
0
pH
l e
Salinity
Temp
g
b
a
f k d
−1
OM Size
c
DO
Chl a
−3
−2
−1
0
1
2
0.8
Chlorophyll a concentration (μg L–1)
3
Biogeography of cyanobacteria in coastal Hawaii
Control High-impact Low-impact b
0.6 ab
0.4 a
0.2
a
ab
b
0.0
3
0
3
6
9
pH
DO
Chl a
TSM Temp
j ih g
0
δ15N
Salinity
a b c d e f g h i j k l
cf
−1
CCA2
1
ab l e
−2
d k
−2
−1
Water Column
0
1
2
Anaehoomalu Bay A Anaehoomalu Bay B Honaunau A Honaunau B Kiholo North Kiholo South Kohala Mahukona Pololu Puako A Puako B Spencer
3
4
CCA1 Fig. 2. CCA of sediment and water column cyanobacterial communities fitted to biotic and abiotic predictor variables. Vector length and direction indicate relative influence on community structure; letters represent weighted averages for species at each site.
Cyanobacterial abundance in the low-impact treatment increased to 43 920 2935 cells mL1 on day 3, consistent with the chlorophyll a spike observed in the lowimpact treatment on day 3 (Fig. 4). Species richness and Simpson diversity index did not vary significantly with time or across treatments in mesocosm incubations. Increases in species richness and Simpson diversity index occurred in all treatments between day 1 and 3. Increased levels of diversity were lost in control and low-impact treatments, and increased diversity was maintained in the high-impact treatment.
Discussion Bray–Curtis dissimilarity indices suggest that compositionally distinct cyanobacterial communities exist between the water column and sediments (Fig. 1). Differences in bacterial community composition between the water FEMS Microbiol Ecol 89 (2014) 80–88
Fig. 3. Chlorophyll a concentration (lg L1) at different sampling time points in mesocosm treatments. High-impact treatment was amended with freshwater from Spencer Beach, low-impact treatment was amended with freshwater from an anchialine pool, and control received no freshwater addition. Letters indicate significant differences within each time point determined by Tukey’s HSD (P < 0.05). Means and standard error are presented for each time point (n = 2).
Cyanobacterial abundance (cells mL–1)
2
Time (Days)
Control High-impact Low-impact
40 000
30 000
20 000
10 000
0
0
3
6
9
Time (Days) Fig. 4. Cyanobacterial abundance (cells mL1) at different sampling time points in mesocosm treatments. High-impact treatment was amended with freshwater from Spencer Beach, low-impact treatment was amended with freshwater from an anchialine pool, and control received no freshwater addition. Means and standard error are presented for each time point (n = 2).
column and sediments have been previously observed in marine ecosystems (Stevens et al., 2005; Hewson & Fuhrman, 2006a; Lozupone & Knight, 2007). These observations were further supported by CCAs, which show clear differences in water column and sediment community structure (Fig. 2). Increased species richness and diversity ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
86
were found in sediments, which follows previous observations of high levels of microbial diversity in sediment ecosystems (Lozupone & Knight, 2007). Distinct communities were not observed between surface (0–2 cm) and deep (12–14 cm) sediment profiles (Fig. 1), although community structuring between surface and deep sediments is a feature observed in other marine and reef environments (Hewson & Fuhrman, 2006a; Hewson et al., 2007). Here, a lack of community structure between sediment profiles potentially indicates homogenization between surface and deep sediment profiles. This is likely due to mixing between these profiles, as sediments were collected in c. 2 m of water in areas of high surf and tidal action. Bioturbation by burrowing organisms may have caused homogenization of deep and shallow sediment horizons. Based on our observations, cyanobacterial community composition corresponds most strongly with overall biomass (inferred from chlorophyll a concentration) and less strongly with other measured environmental parameters. CCA results also indicate that sediment and water column communities may respond differently to biotic/abiotic variables and environmental conditions. In sediments, chlorophyll a, d15N, TSM, and temperature were the strongest predictors of community structure, while in the water column, chlorophyll a and pH were the strongest predictors of community structure (Fig. 2). The correspondence of d15N and TSM to sediment OTUs may indicate the influence of anthropogenic nutrient loading on sediment cyanobacterial communities. Chlorophyll a concentration (overall biomass) was the strongest predictor of community composition in both sediment and water column, and it corresponded strongly to unique community assemblages in both environments (Fig. 2). Productive nearshore environments may favor particular community assemblages of cyanobacteria that are not dominant in oligotrophic marine systems. This may reflect the transition between oligotrophic openocean cyanobacterial communities and those more typical of mesotrophic coastal conditions present in fringing coral reef habitats. These results are in line with the general observation of transitions from Prochlorococcus-dominant open-ocean waters to Synechococcus-dominant coral reef ecosystems (Charpy & Blanchot, 1998, 1999) and other observations of distinct cyanobacterial community structuring at the freshwater–seawater interface (Hewson et al., 2006a, 2007). Bacterial community richness and diversity have been shown to increase with productivity in a number of marine ecosystems (Horner-Devine et al., 2004; Hewson et al., 2006a, b, 2007; Hewson & Fuhrman, 2007). Our mesocosm results indicate that as water column chlorophyll a concentration and overall biomass increase ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
(Fig. 3), cyanobacterial abundance decreases (Fig. 4). It is therefore likely that other phytoplankton outcompete cyanobacteria in experimental mesocosms. Variable response between treatments indicates that input from sources of variable quality may have differential effects on reef cyanobacterial communities. Specifically, we observed a large spike in cyanobacterial abundance on day 3 of the low-impact freshwater-amended treatment (Fig. 4), although in all treatments cyanobacterial abundance decreased to similar levels by the end of incubation. Extending our results to coastal phytoplankton, it is possible that when a coastal zone receives an initial pulse of groundwater discharge, cyanobacterial populations will increase, but over longer periods or with chronic loading, more competitive phytoplankton populations replace cyanobacteria. The similar response of cyanobacteria to both inputs suggests a general response of marine cyanobacteria to coastal freshwater input. Comparison of mesocosm observation with water column CCA shows that while community structuring is primarily related to chlorophyll a concentration and productivity (Fig. 2), a particular water column cyanobacterial community assemblage may be favored in coastal systems where cyanobacteria are outcompeted by eukaryotic phytoplankton. These observations support the idea that oligotrophic open-ocean cyanobacterial communities may be replaced by unique communities when in contact with coastal zones of groundwater discharge, such as Hawaii’s west coast. Our results suggest that cyanobacterial communities in the water column and sediments of the fringing coral reef are distinct and that their community structure is related to the overall biomass and productivity of their ecosystems. However, our results also highlight strong site-specific heterogeneity in composition that is related to localized abiotic and biotic factors. Benthic and planktonic cyanobacterial communities correspond to separate sets of environmental variables, and as a result, these communities likely respond differentially to environmental change. Furthermore, our results provide evidence that terrestrial inputs may cause changes to the composition and abundance of cyanobacterial communities, leading to communities that are distinct from open-ocean ecosystems. Hence, as expected, increased human development in catchments that influence freshwater discharge into coastal zones (Dollar & Atkinson, 1992; Knee et al., 2010) may restructure pelagic, oligotrophic cyanobacterial communities advected from the open ocean. Moreover, our results suggest that cyanobacteria inhabiting the fringing reefs of Hawaii are sensitive to freshwater inputs, and planktonic and benthic cyanobacterial communities may exhibit distinct community responses to environmental change. FEMS Microbiol Ecol 89 (2014) 80–88
Biogeography of cyanobacteria in coastal Hawaii
Acknowledgements We thank the Department of Ecology and Evolutionary Biology at Cornell University for funding and support. The authors thank N. Hairston, J. Sparks, and the students of Cornell Graduate Tropical Field Ecology, January 2013, for assistance with sample collection, transport, and processing. This work was supported by NSF grant OCE 0961894 awarded to IH.
References Azam F & Malfatti F (2007) Microbial structuring of marine ecosystems. Nat Rev Microbiol 5: 782–791. Brown MV, Schwalbach MS, Hewson I & Fuhrman JA (2005) Coupling 16S-ITS rDNA clone libraries and ARISA to show marine microbial diversity: development and application to a time series. Environ Microbiol 7: 1466–1479. Bureau UC (2010) Statewide Population Growth Rates. Hawai’i State Department of Business, Economic Development & Tourism, Suitland, MD, USA. Charpy L (1996) Phytoplankton biomass and production in two Tuamotu atoll lagoons (French Polynesia). Mar Ecol Prog Ser 145: 133–142. Charpy L (2005) Importance of photosynthetic picoplankton in coral reef ecosystems. Vie Milieu 55: 217–224. Charpy L & Blanchot J (1998) Photosynthetic picoplankton in French Polynesian atoll lagoons: estimation of taxa contribution to biomass and production by flow cytometry. Mar Ecol Prog Ser 162: 57–70. Charpy L & Blanchot J (1999) Picophytoplankton biomass, community structure and productivity in the Great Astrolabe Lagoon, Fiji. Coral Reefs 18: 255–262. Charpy L, Palinska KA, Casareto B, Langlade MJ, Suzuki Y, Abed RMM & Golubic S (2009) Dinitrogen-fixing cyanobacteria in microbial mats of two shallow coral reef ecosystems. Microb Ecol 59: 174–186. Charpy L, Casareto BE, Langlade MJ & Suzuki Y (2012) Cyanobacteria in coral reef ecosystems: a review. J Mar Biol 2012: 1–9. Charpy-Roubaud C & Larkum AWD (2005) Dinitrogen fixation by exposed communities on the rim of Tikehau atoll (Tuamotu Archipelago, French Polynesia). Coral Reefs 24: 622–628. Charpy-Roubaud C, Charpy L & Larkum A (2001) Atmospheric dinitrogen fixation by benthic communities of Tikehau Lagoon (Tuamotu Archipelago, French Polynesia) and its contribution to benthic primary production. Mar Biol 139: 991–998. Clague DA, Dalrymple GB & Moberly R (1975) Petrography and K-Ar ages of dredged volcanic rocks from the western Hawaiian Ridge and the southern Emperor Seamount chain. Geol Soc Am Bull 86: 991–998. Dailer ML, Knox RS, Smith JE, Napier M & Smith CM (2010) Using d15N values in algal tissue to map locations and
FEMS Microbiol Ecol 89 (2014) 80–88
87
potential sources of anthropogenic nutrient inputs on the island of Maui, Hawai’i, USA. Mar Pollut Bull 60: 655–671. Dean WE (1974) Determination of carbonate and organic matter in calcareous sediments and sedimentary rocks by loss on ignition; comparison with other methods. J Sediment Res 44: 242–248. Dollar SJ & Atkinson MJ (1992) Effects of nutrient subsidies from groundwater to nearshore marine ecosystems off the island of Hawaii. Estuar Coast Shelf Sci 35: 409–424. Dong J, Zhang Y, Wang Y, Zhang S & Wang H (2008) Spatial and seasonal variations of cyanobacteria and their nitrogen fixation rates in Sanya Bay, South China Sea. Sci Mar 72: 239–251. Dufour P, Andrefou€et S, Charpy L & Garcia N (2001) Atoll morphometry controls lagoon nutrient regime. Limnol Oceanogr 46: 456–461. Field CB (1998) Primary production of the biosphere: integrating terrestrial and oceanic components. Science 281: 237–240. Fisher MM & Triplett EW (1999) Automated approach for ribosomal intergenic spacer analysis of microbial diversity and its application to freshwater bacterial communities. Appl Environ Microbiol 65: 4630–4636. Gonzalez JM, Torreton J-P, Dufour P & Charpy L (1998) Temporal and spatial dynamics of the pelagic microbial food web in an atoll lagoon. Aquat Microb Ecol 16: 53–64. Guilherme Becker C, Dalziel BD, Kersch Becker MF, Park MG & Mouchka M (2013) Indirect effects of human development along the coast on coral health. Biotropica 45: 401–407. Hewson I & Fuhrman JA (2004) Richness and diversity of bacterioplankton species along an estuarine gradient in Moreton Bay, Australia. Appl Environ Microbiol 70: 3425– 3433. Hewson I & Fuhrman JA (2006a) Spatial and vertical biogeography of coral reef sediment bacterial and diazotroph communities. Mar Ecol Prog Ser 306: 79–86. Hewson I & Fuhrman JA (2006b) Viral impacts upon marine bacterioplankton assemblage structure. J Mar Biol Assoc UK 86: 577–589. Hewson I & Fuhrman JA (2007) Covariation of viral parameters with bacterial assemblage richness and diversity in the water column and sediments. Deep Sea Res Part I 54: 811–830. Hewson I, O’Neil JM, Fuhrman JA & Dennison WC (2001) Virus-like particle distribution and abundance in sediments and overlying waters along eutrophication gradients in two subtropical estuaries. Limnol Oceanogr 46: 1734–1746. Hewson I, Capone DG, Steele JA & Fuhrman JA (2006a) Influence of Amazon and Orinoco offshore surface water plumes on oligotrophic bacterioplankton diversity in the west tropical Atlantic. Aquat Microb Ecol 43: 11–22. Hewson I, Steele JA, Capone DG & Fuhrman JA (2006b) Remarkable heterogeneity in meso- and bathypelagic bacterioplankton assemblage composition. Limnol Oceanogr 51: 1274–1283.
ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
88
Hewson I, Jacobson Meyers ME & Fuhrman JA (2007) Diversity and biogeography of bacterial assemblages in surface sediments across the San Pedro Basin, Southern California Borderlands. Environ Microbiol 9: 923–933. Horner-Devine MC, Carney KM & Bohannan BJM (2004) An ecological perspective on bacterial biodiversity. Proc R Soc Lond B Biol Sci 271: 113–122. Kayanne H, Hirota M, Yamamuro M & Koike I (2005) Nitrogen fixation of filamentous cyanobacteria in a coral reef measured using three different methods. Coral Reefs 24: 197–200. Knee K, Street JH, Grossman EG & Paytan A (2010) Nutrient inputs to the coastal ocean from submarine groundwater discharge in a groundwater-dominated system: relation to land use (Kona coast, Hawaii, U.S.A.). Limnol Oceanogr 55: 1105–1122. Lapointe BE & Bedford BJ (2011) Stormwater nutrient inputs favor growth of non-native macroalgae (Rhodophyta) on O’ahu, Hawaiian Islands. Harmful Algae 10: 310–318. Lozupone CA & Knight R (2007) Global patterns in bacterial diversity. P Natl Acad Sci USA 104: 11436–11440. Parsons TR, Maita Y & Lalli CM (1985) A Manual of Chemical and Biological Methods for Seawater Analysis. Pergamon Press, Oxford.
ª 2014 Federation of European Microbiological Societies. Published by John Wiley & Sons Ltd. All rights reserved
S.D. Chamberlain et al.
Parsons ML, Walsh WJ, Settlemier CJ, White DJ, Ballauer JM, Ayotte PM, Osada KM & Carman B (2008) A multivariate assessment of the coral ecosystem health of two embayments on the lee of the island of Hawai’i. Mar Pollut Bull 56: 1138–1149. Peterson RN, Burnett WC, Glenn CR & Johnson A (2009) Quantification of point-source groundwater discharges to the ocean from the shoreline of the Big Island, Hawaii. Limnol Oceanogr 54: 890–904. R Core Team (2013) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria. Rocap G, Distel DL, Waterbury JB & Chisholm SW (2002) Resolution of Prochlorococcus and Synechococcus ecotypes by using 16S–23S ribosomal DNA internal transcribed spacer sequences. Appl Environ Microbiol 68: 1180–1191. Stevens H, Brinkhoff T & Simon M (2005) Composition of free-living, aggregate-associated and sediment surface-associated bacterial communities in the German Wadden Sea. Aquat Microb Ecol 38: 15–30. Street JH, Knee KL, Grossman EE & Paytan A (2008) Submarine groundwater discharge and nutrient addition to the coastal zone and coral reefs of leeward Hawai’i. Mar Chem 109: 355–376.
FEMS Microbiol Ecol 89 (2014) 80–88
