Figures
Abstract
Heterotrophic microbial communities cycle nearly half of net primary productivity in the ocean, and play a particularly important role in transformations of dissolved organic carbon (DOC). The specific means by which these communities mediate the transformations of organic carbon are largely unknown, since the vast majority of marine bacteria have not been isolated in culture, and most measurements of DOC degradation rates have focused on uptake and metabolism of either bulk DOC or of simple model compounds (e.g. specific amino acids or sugars). Genomic investigations provide information about the potential capabilities of organisms and communities but not the extent to which such potential is expressed. We tested directly the capabilities of heterotrophic microbial communities in surface ocean waters at 32 stations spanning latitudes from 76°S to 79°N to hydrolyze a range of high molecular weight organic substrates and thereby initiate organic matter degradation. These data demonstrate the existence of a latitudinal gradient in the range of complex substrates available to heterotrophic microbial communities, paralleling the global gradient in bacterial species richness. As changing climate increasingly affects the marine environment, changes in the spectrum of substrates accessible by microbial communities may lead to shifts in the location and rate at which marine DOC is respired. Since the inventory of DOC in the ocean is comparable in magnitude to the atmospheric CO2 reservoir, such a change could profoundly affect the global carbon cycle.
Citation: Arnosti C, Steen AD, Ziervogel K, Ghobrial S, Jeffrey WH (2011) Latitudinal Gradients in Degradation of Marine Dissolved Organic Carbon. PLoS ONE 6(12): e28900. https://doi.org/10.1371/journal.pone.0028900
Editor: Meni Wanunu, Northeastern University, United States of America
Received: June 15, 2011; Accepted: November 16, 2011; Published: December 28, 2011
Copyright: © 2011 Arnosti et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: This work was supported by the National Science Foundation (Dr. Arnosti, Dr. Jeffrey), EPA Graduate Fellowship (Dr. Steen), and the Deutsche Forschungsgemeinschaft Postdoctoral Fellowship (Dr. Ziervogel). The authors are also grateful to the Max-Planck Institute for Marine Microbiology (Bremen) for supporting the work on Svalbard. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Introduction
Marine DOC (dissolved organic carbon) is one of the largest actively cycling reservoirs of organic carbon on earth, comparable in magnitude to the atmospheric reservoir of CO2 [1]; heterotrophic microbial communities play a key role in driving the DOC cycle [2]–[4]. DOC consists of many thousands of different compounds, and is operationally divided into labile, semi-labile, and recalcitrant fractions that are defined based on timescales of removal in bioassays or by direct measurement in the ocean [5]. Structural or mechanistic explanations for varying timescales of DOC degradation, however, are lacking [6]. Since heterotrophic bacteria are unable to transport directly into the cell most substrates with a molecular weight greater than 600 Da [7], hydrolysis via extracellular enzymes is required prior to substrate uptake. The requirement for enzymatic hydrolysis is therefore a promising starting point to search for mechanistic explanations of variations in the abilities of marine bacteria to utilize specific fractions of DOC as a substrate. The activities and structural specificities of polysaccharide-hydrolyzing enzymes are of particular importance in this respect, since carbohydrates constitute a large proportion of marine high molecular weight DOC: 54% of surface water DOC and 25% of DOC in the deep ocean [8]. Most of the rest of DOC is classified as ‘uncharacterized’ on a molecular basis, since lipids, amino acids, and amino sugars together constitute less than ca. 5% of the total [9].
Assessing the enzymatic capabilities of marine heterotrophic microbial communities can best be done directly in seawater, since cultured microbial isolates constitute only a small, unrepresentative fraction of extent marine microbes [10]. Most measurements of enzyme activity in seawater are based on small chromogenic or fluorogenic substrates (e.g. [11]), which provide very little information about enzymatic substrate specificities [12]. Genomic investigations can yield valuable insights into community and organism potential [13]–[15], but provide no information about the extent to which such potential might be expressed. Metatranscriptomic profiling is a promising route to investigate the extent to which genetic potential is realized, but assignment of sequences from the environment to functions such as specific enzyme activities is still problematic due to limitations in database coverage [16] and the vast structural and functional diversity of polysaccharide-hydrolyzing enzymes [17].
To gain insight into the capabilities of natural microbial communities to access polysaccharides, we measured extracellular enzyme activities in surface waters at 32 stations in the Atlantic, Pacific, Arctic, and Southern Oceans, as well as the Gulf of Mexico, spanning latitudes from 76°S to 79°N and a temperature range from −1.8°C to 29°C (Table 1; Fig. S1). We focused on direct detection of the hydrolysis of specific polysaccharides, rather than on investigations of genetic potential, in order to measure the abilities of microbial communities to access substrates irrespective of the multiplicity of enzyme(s) [18] —of known and unknown sequence—that might hydrolyze a specific substrate. Since determining the specific structures of marine dissolved carbohydrates is not possible using currently available analytical techniques [19], we used as substrates a suite of polysaccharides that are components of marine algae [20], and/or whose hydrolytic enzymes have been identified in the genomes of recently-sequenced marine bacteria [13], [15], [21]. These polysaccharides—laminarin, xylan, fucoidan, arabinogalactan, pullulan, and chondroitin sulfate—are structurally diverse, vary in monomer composition and linkage position, and because they are constituents of marine plankton, many are present in considerable quantities in the ocean. The production of laminarin by diatoms and Phaeocystis in the ocean, for example, has been estimated at 5 to15 billion metric tons annually [22]. A previous investigation at a few locations had shown evidence of spatial variations in microbial extracellular enzyme activities in surface ocean waters [23]. The present study, the culmination of a series of investigations carried out over the course of a decade, demonstrates that there are recognizable patterns in microbial potential to access DOC on large-scale gradients, mirroring emerging patterns of microbial biogeography in the ocean [24]–[28].
Results and Discussion
Differing abilities to hydrolyze a diverse range of substrates, as evident in our survey (Fig. 1), demonstrate functional differences among pelagic microbial communities. All substrates were hydrolyzed at only 4 of the 32 stations, all in the Gulf of Mexico. At the other 28 sites, the spectrum of hydrolysis ranged from one to five substrates. Only laminarin was hydrolyzed at every station; chondroitin and xylan were hydrolyzed at the majority (81% and 78%, respectively) of the stations, while pullulan, arabinogalactan, and fucoidan were hydrolyzed at 63%, 47%, and 34% of the stations, respectively. Summed hydrolysis rates were maximal at tropical/subtropical stations, and these summed rates as well as the spectrum of detected enzyme activities, decreased towards the poles (Figs. 1 and 2). The relative contribution of each enzyme activity to the sum at a given station (evenness of hydrolysis rates; Fig. 3) showed a similar pattern, with increasing evenness at higher temperatures (and lower latitudes).
Bar height shows the sum of the maximum enzymatic hydrolysis rate of each substrate at each station. All stations were visited once, with the exception of Station J (79°N); values shown for Station J are averages from 4 visits. (See Fig. 4 and Table S1 for data from each sampling time at Station J.) Pullulan hydrolysis is shown in blue, laminarin in yellow, xylan in red, fucoidan in green, arabinoglactan in white, and chondroitin sulfate in aqua. Hydrolysis rates and standard deviations for all substrates and stations are in Table S1.
Station latitude and color key for enzyme identity are as in Fig. 2.
Average values (as shown in Figs. 1 and 2) were used for Station J, the only station that was sampled more than once. Line fit: r2 = 0.6154, n = 26, p<0.001.
The broad correlation between latitude and summed hydrolysis rates points to the relationship between summed hydrolysis rates and water temperature (n = 35, including 4 visits to a single station (Station J; Table 1), r2 = 0.64, p<0.005), a relationship that could be due to the kinetic effect of temperature. This correlation, however, is driven primarily by the correlation with laminarin (r2 = 0.79; p<0.005) and by the fact that a broader spectrum of enzyme activities is detected across the range of stations in lower-latitude waters (Figs. 1 and 2). Temperature was poorly correlated with hydrolysis of chondroitin (r2 = 0.15; p<0.05), arabinogalactan and pullulan (r2 = 0.20 and 0.21, respectively; p<0.01), and fucoidan (r2 = 0.23, p<0.005). The correlation with xylan was stronger (r2 = 0.49, p<0.005), but hydrolysis rates of the substrates at stations with similar temperatures varied greatly. At temperatures close to 28°C, for example, the variation in hydrolysis of xylan, fucoidan, arabinogalactan, and chondroitin was an order of magnitude or more (Table 1; Table S1; Fig. 1). Moreover, the differences in hydrolysis rate evenness (Fig. 3) are not explained solely by temperature, since a purely kinetic effect of temperature on hydrolysis rates would be expected to cause a generally proportionate change in the activities of all enzymes, and greatly extended incubation times do not markedly broaden the spectrum of substrates hydrolyzed at high latitude [29].
To the extent that these differences in enzymatic capabilities cannot be explained by temperature, they may derive from variations in microbial community composition that cascade into these functional differences. Arctic microbial communities differ in composition from their temperate counterparts [24], [30]–[31]. Recent investigations have demonstrated latitudinal gradients in microbial community richness, with markedly reduced diversity at high latitudes [26]–[28]. The functional consequences of these variations are unknown, since microbial phylogeny and function are not well correlated. Our results demonstrate that microbial community function varies systematically across latitudinal gradients. The lower summed hydrolysis rates and the more limited spectrum of substrates enzymatically accessible to microbial communities at high latitudes coincides with a reduction in community richness (Figs. 1 and 2).
Differences in the extent to which genes for polysaccharide hydrolases are expressed may also contribute to differences in enzyme activities among microbial communities, but the genetic diversity of polysaccharide hydrolases even among well-studied organisms is barely beginning to be explored [32], complicating efforts for a concerted genetic investigation. One study suggests that a high diversity of hydrolases is potentially available to microbial communities in the North Atlantic [14], but the extent and the conditions under which this genetic potential might be expressed are still matters of speculation. A search of the CAMERA database (http://camera.calit2.net/), for example, yielded numerous gene sequences related to an alpha-l-fucosidase of Pseudoalteromonas atlantica T6c (http://img.jgi.doe.gov/cgi-bin/pub/main.cgi). These sequences were found at 60 different Global Ocean Survey (GOS) sites (available through CAMERA), spanning latitudes of 32°S to 45°N, despite the fact that this enzyme activity was not detected in many of our samples from the same range of latitudes (Fig. 1). Likewise, a search (via CAMERA) of the two marine sites in the Antarctic Aquatic Metagenome produced sequences from Newcomb Bay (66°S) closely matching pullulanases from fully-sequenced marine bacteria (http://blast.ncbi.nlm.nih.gov/Blast.cgi), although pullulanase activity was not detectable at any of our sites at latitudes higher than 49°S or 38°N (Fig. 1). Limited geographical overlap between the current CAMERA database and our samples presently preclude a more detailed comparison among sites that would provide insight into the extent to which microbial communities vary in their genetic response to environmental parameters.
Patterns of microbial community composition at a given location are temporally repeatable [33]–[37]. Results from our investigation suggest that patterns of hydrolytic activities are also consistent over multi-year timescales. One high-latitude station (79°N, Stn. J; Table 1) sampled four times over the course of 10 years consistently showed hydrolytic activity dominated by chondroitinase (>50% of total activity), with similar patterns and levels of total activity (Table S1; Fig. 4). Likewise, two pairs of stations close to one another in the Gulf of Mexico (GOM1 and GOM11, 28°N; also GOM072 and GOM073, 28.2–30.2°N; Table 1) sampled 6 years apart showed the same broad substrate spectrum (nearly unique among sample locations; Fig. 2) and high levels of total activity (Fig. 1).
Each enzyme activity is shown in a different color; summed rates are normalized to 1.0. Pullulan hydrolysis is shown in blue, laminarin in yellow, xylan in red, fucoidan in green, arabinoglactan in white, and chondroitin sulfate in aqua. All rates plus standard deviations are listed in Table S1.
The patterns in enzymatic activities observed here provide insight into the potential of microbial communities to access components of the DOC pool, rather than a snapshot of enzyme activities expressed at the time of sampling, since our enzyme incubations lasted several days to two weeks. These experiments demonstrate the potential of a microbial community to access specific substrates over timescales sufficiently long to allow for cellular growth as well as for enzyme induction. The observation that many substrates remained unhydrolyzed over these timescales suggests that some microbial communities collectively lack the capabilities (enzymes, inducers, or organisms) to access specific substrates [38].
This information is unique, since no other currently available analytical method tests the abilities of microbial communities to access specific polysaccharide structures. Likewise, the concentrations of specific polysaccharides in the ocean cannot be measured with currently-available techniques [19], precluding direct measurement of polysaccharide production or concentration. Comparable data cannot be obtained by measuring surface water DOC concentrations at diverse locations, because DOC concentrations are a function of DOC production, DOC degradation, and water mass history [39] (the radiocarbon age of bulk DOC is ca. 6000 years [40].) Measurements of DOC concentrations in the surface ocean therefore cannot differentiate unambiguously between changes in the metabolic capabilities of heterotrophic microbes, changes in DOC production, and differences in water mass history. Moreover, attempts to constrain production and consumption terms for DOC across broad latitudinal gradients are greatly complicated by the multitude of sources and varying bioavailabilities of different components of the DOC pool [6], as well as the paucity of data from high latitude environments [9], [41]. A measure of the spectrum of enzyme activities capable of hydrolyzing a class of biomolecules constituting the largest identified component of the DOC pool thus yields insight into processes otherwise not amenable to quantification.
The broader spectrum of enzyme activities observed at temperate and tropical sites indicates that those microbial communities can access a wider range of substrates than their high-latitude counterparts. The fact that this trend was discernable in our global data set despite variations in season, levels of productivity, oceanic province, and a host of other factors, is remarkable. The functional factors controlling the breadth of microbial community metabolic capabilities remain to be determined. However, the pattern observed here matches the decrease in bacterial species richness observed at high latitudes [26]–[27]. The reason for that trend is not well understood [42]; bacterial richness correlates to a similar extent with water temperature and latitude [26]. A recent model investigation of global patterns of phytoplankton diversity, however, points at the magnitude of seasonal variability in environments and at relative rates of organism dispersal as key factors controlling latitudinal diversity gradients for phytoplankton [43]. Similar factors may control diversity gradients of heterotrophic bacteria.
Projected changes in ocean environments over the coming decades driven by global warming [44]–[45] may increase the rates and widen the spectrum of enzyme activities due to changes in microbial community composition that are facilitated by changes in ocean temperature, circulation, or biogeochemical parameters [46]. Particularly in the Arctic, where rapid temperature increases are projected for the near future, the input of terrestrially-derived DOC into the Arctic basin may be greatly accelerated due to melting of permafrost and increased runoff [47]. Currently, much of this organic matter is buried or exported to the North Atlantic [41], [48]–[49]. In the future, more organic matter may reach the Arctic Ocean, and if the range of complex substrates available to heterotrophic microbial communities is broader in a future Arctic Ocean, a larger fraction of it may be remineralized there.
Kirchman et al. [46] predict that climate change in polar waters may also lead to changes in food web structure resulting in greater transfer of carbon from phytoplankton to DOC to bacteria, and thus to the respiration of a larger fraction of marine primary production to CO2. These processes would be greatly facilitated if future polar microbial communities can use a wider range of enzymatic tools, as their temperate to tropical counterparts currently do. Since DOC reactivity is a function of the metabolic capabilities of microbial communities as well as intrinsic chemical characteristics, predictive understanding of the global carbon cycle will require further investigation of the ways in which these metabolic capabilities are likely to change in response to changing climate.
Materials and Methods
Sample collection, substrate incubation, and sample analysis
Surface water was collected at each site (Table 1; Fig. S1), by Niskin or Go-Flo bottles; surface water at Stns. J and AB was collected by bucket. Water samples were dispensed into replicate vials. Each vial received a single fluorescently labeled polysaccharide [50] as a substrate, at a concentration of 3.5 µmol monomer equivalent L−1. Triplicate vials were incubated at in situ temperature. Controls were autoclaved or poisoned with mercuric chloride before substrate addition. Subsamples from each vial were filtered through 0.2 µm pore-sized filters, and were stored frozen prior to analysis. Changes in substrate molecular weight with time were quantified using gel permeation chromatography, with Sephadex G-50 and G-75 columns linked in series, and fluorescence detection (excitation and emission wavelengths of 490 and 530 nm, respectively), as previously described [51]. Hydrolysis rates were calculated from changes in molecular weight distribution of the polysaccharides, as described previously [50]–[51]. No specific permits were required for the collection of water from the ocean as described above. The field studies did not involve any endangered or protected species.
Statistical analyses
Statistical comparisons were carried out using two-tailed Student's t-test. The evenness of hydrolysis rates (the contribution of each activity to summed activities) was calculated using Shannon's entropy [52], , where fi represents the hydrolysis rate of the ith substrate expressed relative to the sum of all hydrolysis rates for that station. As previously discussed [53], H is maximized (H≈1.79) when enzymatic hydrolysis rates of all substrates are equal, and minimized (H = 0) when only one hydrolysis rate was measurable. Error bars in Fig. 3 represent the standard deviation of the ensemble results from a Monte Carlo error simulation, as described in [53].
Supporting Information
Table S1.
Sampling dates and rates of enzymatic hydrolysis (nmol monomer L−1 h−1) of all substrates at all stations, including standard deviations of triplicate incubations.
https://doi.org/10.1371/journal.pone.0028900.s002
(DOC)
Acknowledgments
We thank the captains, crews, and scientific parties of R/V Farm, R/V Cape Hatteras, R/V Cape Henlopen, R/V N.B. Palmer, R/V Hugh Sharp, and R/V Pelican for help with sampling, and A.J. Baldwin for her assistance with shipboard experiments.
Author Contributions
Conceived and designed the experiments: CA WHJ. Performed the experiments: CA ADS KZ SG WHJ. Analyzed the data: CA ADS KZ SG. Wrote the paper: CA. Contributed to writing the manuscript: ADS KZ SG WHJ. Performed statistical analyses: ADS KZ.
References
- 1.
Hedges JI (2002) Why dissolved organics matter. In: Hansell DA, Carlson CA, editors. Biogeochemistry of Marine Dissolved Organic Matter. San Diego: Academic Press. pp. 1–33.
- 2. Azam F (1998) Microbial control of oceanic carbon flux: The plot thickens. Science 280: 694–696.
- 3.
Hansell DA, Carlson C (2002) Biogeochemistry of Dissolved Organic Matter. San Diego: Academic Press.
- 4. McCarren J, Becker JW, Repeta DJ, Shi Y, Young CR, et al. (2010) Microbial community transcriptomes reveal microbes and metabolic pathways associated with dissolved organic matter turnover in the sea. PNAS.
- 5.
Carlson CA (2002) Production and removal processes. In: Hansell DA, Carlson CA, editors. Biogeochemistry of Dissolved Organic Matter. San Diego: Academic Press. pp. 91–139.
- 6. Jiao N, Herndl GJ, Hansell DA, Benner R, Kattner G, et al. (2010) Microbial production of recalcitrant dissolved organic matter: long-term carbon storage in the global ocean. Nature Rev Microbiol 8: 593–599.
- 7. Weiss MS, Abele U, Weckesser J, Welte W, Schiltz E, et al. (1991) Molecular architecture and electrostatic properties of a bacterial porin. Science 254: 1627–1630.
- 8. Benner R, Pakulski JD, McCarthy M, Hedges JI, Hatcher PG (1992) Bulk chemical characteristics of dissolved organic matter in the ocean. Science 255: 1561–1564.
- 9.
Benner R (2002) Chemical composition and reactivity. In: Hansell DA, Carlson CA, editors. Biogeochemistry of Marine Dissolved Organic Matter. New York: Academic Press. pp. 59–90.
- 10. DeLong EF, Pace N (2001) Environmental diversity of bacteria and archea. Syst Biol 50: 470–478.
- 11. Hoppe H-G (1983) Significance of exoenzymatic activities in the ecology of brackish water: measurements by means of methylumbelliferyl-substrates. Mar Ecol Prog Ser 11: 299–308.
- 12.
Arnosti C (2011) Microbial extracellular enzymes and the marine carbon cycle,. In: Carlson C, Giovannoni S, editors. (2011) Annual Review of Marine Science, vol 3. Palo Alto: Annual Reviews. pp. 401–425.
- 13. Bauer M, Kube M, Telling H, Richter M, Lombardot T, et al. (2006) Whole genome analysis of the marine Bacteroidetes ‘Gramella forsetii’ reveals adaptations to degradation of polymeric organic matter. Environmental Microbiology 8: 2201–2213.
- 14. Elifantz H, Waidner LA, Michelou VK, Cottrell MT, Kirchman DL (2008) Diversity and abundance of glycosyl hydrolase family 5 in the North Atlantic Ocean. FEMS Microbiol Ecol 63: 316–327.
- 15. Weiner RM, Taylor LE II, Henrissat B, Hauser L, Land M, et al. (2008) Complete genome sequence of the complex carbohydrate-degrading marine bacterium, Saccharophagus degradans Strain 2-40T. PLOS Genetics 5(5): e1000087.
- 16. Gilbert J, Field D, Swift P, Simon T, Cummings D, et al. (2010) Taxonomic and functional diversity of microbes at a temperate coastal site: A ‘multi-omic’ study of seasonal and diel temporal variation. PLoS ONE 5(11): e15545.
- 17. Cantarel BL, Coutinho PM, Rancurel C, Bernard T, Lombard V, et al. (2008) The carbohydrate-active enzyme database (CAZy): an expert resource for glycogenomics. Nucleic Acids Res 37: 233–38.
- 18. Arrieta JM, Herndl GJ (2002) Changes in bacterial β-glucosidase diversity during a coastal phytoplankton bloom. Limnol Oceanogr 47: 594–599.
- 19. Hedges JI, Eglinton G, Hatcher PG, Kirchman DL, Arnosti C, et al. (2000) The Molecularly-uncharacterized component (MUC) of nonliving organic matter in natural environments. Organic Geochem 31: 945–958.
- 20.
Painter TJ (1983) Algal Polysaccharides. In: Aspinall GO, editor. The Polysaccharides. New York: Academic Press. pp. 195–285.
- 21. Glockner FO, Kube M, Bauer M, Teeling H, Lombardot T, et al. (2003) Complete genome sequence of the marine planctomycete Pirellula sp. strain 1. Proc Nat Acad Sci 100: 8298–8303.
- 22. Alderkamp A-C, van Rijssel M, Bolhuis H (2007) Characterization of marine bacteria and the activity of their enzyme systems involved in degradation of the algal storage glucan laminarin. FEMS Microbiol Ecol 59: 108–117.
- 23. Arnosti C, Durkin S, Jeffrey WH (2005) Patterns of extracellular enzyme activities among pelagic marine microbial communities: implications for cycling of dissolved organic carbon. Aq Microb Ecol 38: 135–145.
- 24. Baldwin AJ, Moss JA, Pakulski JD, Catala P, Joux F, et al. (2005) Microbial diversity in a Pacific Ocean transect from the Arctic to Antarctic circles. Aq Microb Ecol 41: 91–102.
- 25. Martiny JBH, Bohannan BJM, Brown JH, Colwell RK, Fuhrman JA, et al. (2006) Microbial biogeography: putting microorganisms on the map. Nature Microb Rev 6: 102–112.
- 26. Fuhrman JA, Steele JA, Hewson I, Schwalbach MS, Brown MV, et al. (2008) A latitudinal diversity gradient in planktonic marine bacteria. Proc Nat Acad Sci 105(22): 7774–7778.
- 27. Pommier T, Canback B, Riemann L, Bostrom KH, Simu K, et al. (2007) Global patterns of diversity and community structure in marine bacterioplankton. Molecular Ecol 16: 867–880.
- 28. Wietz M, Gram L, Jorgensen B, Schramm A (2010) Latitudinal patterns in the abundance of major marine bacterioplankton groups. Aq Microb Ecol 61: 179–189.
- 29. Arnosti C (2008) Functional differences between Arctic sedimentary and seawater microbial communities: Contrasts in microbial hydrolysis of complex substrates. FEMS Microb Ecol 66: 343–351.
- 30. Bano N, Hollibaugh JT (2002) Phylogenetic composition of bacterioplankton assemblages from the Arctic Ocean. Appl Environ Microbiol 68: 505–518.
- 31. Malmstrom RR, Straza TRA, Cottrell MT, Kirchman DL (2007) Diversity, abundance, and biomass production of bacterial groups in the western Arctic Ocean. Aq Microb Ecol 47: 45–55.
- 32. Hess M, Sczyrba A, Egan R, Kim T-W, Chokhawala H, et al. (2011) Metagenomic discovery of biomass-degading genes and genomes from cow rumen. Science 331: 463–467.
- 33. Murray AE, Preston CM, Massana R, Taylor LT, Blakis A, et al. (1998) Seasonal and spatial variability of bacteria and archael assemblages in the coastal waters near Anvers Island, Antarctica. Appl Environ Microbiol 64: 2585–2595.
- 34. Morris RM, Vergin KL, Cho J-C, Rappe M, Carlson CA, et al. (2005) Temporal and spatial response of bacterioplankton lineages to annual convective overturn at the Bermuda Atlantic Time-series Study site. Limnol Oceanogr 50: 1687–1696.
- 35. Kan J, Crump BC, Wang K, Chen F (2006) Bacterioplankton communities in Cheasapeake Bay: Predictable or random assemblages. Limnol Oceanogr 51: 2157–2169.
- 36. Fuhrman JA, Steele JA (2008) Community structure of marine bacterioplankton: patterns, networks, and relationships to function. Aq Microb Ecol 53: 69–81.
- 37. Fuhrman JA, Hewson I, Schwalbach MS, Steele JA, Brown MV, et al. (2006) Annually reoccurring bacterial communities are predictable from ocean conditions. Proc Nat Acad Sci USA 103: 13104–13109.
- 38. Arnosti C (2004) Speed bumps and barricades in the carbon cycle: Substrate structural effects on carbon cycling. Mar Chem 92: 263–273.
- 39. Goldberg SJ, Carlson CA, Bock B, Nelson NB, Siegel DA (2010) Meridional variability in dissolved organic matter stocks and diagenetic state within the euphotic and mesopelagic zone of the North Atlantic subtropical gyre. Mar Chem 119: 9–21.
- 40. Bauer JE, Williams PM, Druffel ERM (1992) 14C activity of dissolved organic carbon fractions in the north-central Pacific and Sargasso Sea. Nature 357: 667–670.
- 41.
Amon RMW (2004) The role of dissolved organic matter for the organic carbon cycle in the Arctic Ocean. In: Stein R, Macdonald RW, editors. The organic carbon cycle in the Arctic Ocean. Berlin: Springer. pp. 83–100.
- 42. Fuhrman JA (2009) Microbial community structure and its functional implications. Nature 459: 193–199.
- 43. Barton AD, Dutkiewicz S, Flierl G, Bragg J, Follows MJ (2010) Patterns of diversity in marine phytoplankton. Science 327: 1509–1511.
- 44. Behrenfeld MJ, O'Malley RT, Siegel DA, McClain CR, Sarmiento JL, et al. (2006) Climate-driven trends in contemporary ocean productivity. Nature 444: 752–755.
- 45. Vezina AF, Hoegh-Guldberg O (2008) Effects of ocean acidification on marine ecosystems: Introduction. Mar Ecol Prog Ser 373: 199–201.
- 46. Kirchman DL, Moran XAG, Ducklow H (2009) Microbial growth in the polar oceans—role of temperature and potential impact of climate change. Nature Rev Microbiol 7: 451–459.
- 47. Stocker TF, Raible CC (2005) Water cycle shifts gear. Nature 434: 830–832.
- 48.
Stein R, Macdonald RW (2004) Organic carbon budget: Arctic Ocean vs. Global Ocean. In: Stein R, Macdonald RW, editors. The organic carbon cycle in the Arctic Ocean. Berlin: Springer. pp. 315–323.
- 49. Benner R, Louchouarn P, Amon RMW (2005) Terrigenous dissolved organic matter in the Arctic Ocean and its transport to surface and deep waters of the North Atlantic. Global Biogeochem Cycles 19: GB2025.
- 50. Arnosti C (1996) A new method for measuring polysaccharide hydrolysis rates in marine environments. Org Geochem 25: 105–115.
- 51. Arnosti C (2003) Fluorescent derivatization of polysaccharides and carbohydrate-containing biopolymers for measurement of enzyme activities in complex media. J Chromatog B 793: 181–191.
- 52.
Legendre P, Legendre L (1998) Numerical Ecology. New York: Elsevier. 853 p.
- 53. Steen AD, Ziervogel K, Arnosti C (2010) Comparison of multivariate microbial datasets with the Shannon Index: an example using enzyme activities from diverse marine environments. Org Geochem 41: 1019–1021.