sources, ages, and alteration of organic matter in...

MA08CH17-Canuel ARI 9 December 2015 17:5

Sources, Ages, and Alteration ofOrganic Matter in EstuariesElizabeth A. Canuel1 and Amber K. Hardison2

1Virginia Institute of Marine Science, College of William & Mary, Gloucester Point,Virginia 23062; email: [email protected] Science Institute, University of Texas at Austin, Port Aransas, Texas 78373;email: [email protected]

Annu. Rev. Mar. Sci. 2016. 8:409–34

First published online as a Review in Advance onSeptember 25, 2015

The Annual Review of Marine Science is online atmarine.annualreviews.org

This article’s doi:10.1146/annurev-marine-122414-034058

Copyright c© 2016 by Annual Reviews.All rights reserved

Keywords

organic carbon, coastal, organic geochemistry, biomarkers, stable isotopes,radiocarbon

Abstract

Understanding the processes influencing the sources and fate of organicmatter (OM) in estuaries is important for quantifying the contributions ofcarbon from land and rivers to the global carbon budget of the coastal ocean.Estuaries are sites of high OM production and processing, and understandingbiogeochemical processes within these regions is key to quantifying organiccarbon (Corg) budgets at the land-ocean margin. These regions providevital ecological services, including nutrient filtration and protection fromfloods and storm surge, and provide habitat and nursery areas for numerouscommercially important species. Human activities have modified estuarinesystems over time, resulting in changes in the production, respiration, burial,and export of Corg. Corg in estuaries is derived from aquatic, terrigenous,and anthropogenic sources, with each source exhibiting a spectrum ofages and lability. The complex source and age characteristics of Corg inestuaries complicate our ability to trace OM along the river–estuary–coastalocean continuum. This review focuses on the application of organicbiomarkers and compound-specific isotope analyses to estuarine environ-ments and on how these tools have enhanced our ability to discern naturalsources of OM, trace their incorporation into food webs, and enhanceunderstanding of the fate of Corg within estuaries and their adjacent waters.

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http://www.annualreviews.org/doi/full/10.1146/annurev-marine-122414-034058


BACKGROUND

Why Estuaries?

Estuaries are among the most diverse and productive marine environments, and they play animportant role in carbon and nutrient biogeochemistry (Bianchi 2006). These systems have servedas cradles of civilizations throughout human history because their high productivity has providedready access to food and energy resources, thereby fueling commerce and development. Useof the coastal zone has increased during recent decades, and coasts are undergoing tremendoussocioeconomic and environmental changes globally (Neumann et al. 2015). This trend is expectedto continue in the future, and human populations and habitats—particularly those in the low-elevation coastal zone—are vulnerable to flooding and other effects of climate change. Humanactivities have perturbed these systems through nutrient enrichment, loss of habitat, alterations inspecies composition and diversity, and changes in the flow of water and sediments from rivers (Diaz& Rosenberg 2008, Lotze et al. 2006). Estuaries are also important zones for organic matter (OM)processing and regions where terrigenous and marine OM mix (Hedges & Keil 1999, Middelburg& Herman 2007). The estuarine carbon cycle is closely linked to anthropogenic changes that areoccurring on land and in the open ocean and are tied to the biogeochemical cycles of nitrogenand phosphorus.

Although estuaries have been widely studied from an ecological perspective, tremendous vari-ation within and across estuarine systems contributes to uncertainty about their role in the carboncycle. These regions are not fully incorporated into climate assessments such as the Intergovern-mental Panel on Climate Change report (IPCC 2013) and are missing from many Earth systemmodels owing to limited data availability and high levels of variability (Hermann et al. 2015).Estuaries process significant quantities of terrestrial and marine OM and play a controlling factorin determining fluxes of dissolved and particulate organic carbon (DOC and POC, respectively)to the coastal ocean as well as fluxes of CO2 to the atmosphere (Figure 1). However, how muchOM is produced, consumed, and transformed within these regions remains among the greatestunknowns in coastal oceanography, and models and budgets for the coastal ocean require a morerigorous understanding of OM dynamics (Bauer et al. 2013, Borges 2005, Chen & Borges 2009).Additionally, because these regions act as both sources and sinks for carbon, improved under-standing of the carbon cycle within these zones is important for understanding and predicting therole of the coastal ocean in taking up anthropogenic CO2 from the atmosphere (Cai 2011, Hedgeset al. 1997).

Factors Shaping Estuarine Systems

Estuaries are present in tropical, temperate, and polar regions and are highly diverse owing to dif-ferences in geomorphology, climate, magnitude of fluvial and tidal forcings, and land use histories(Canuel et al. 2012 and references therein). Interactions between physics and biogeochemistryare complex; they occur at different spatial scales (e.g., estuarine circulation, river and ground-water discharge, tidal flooding, resuspension events, and exchanges with adjacent marsh systems),and the relative importance of these physical forcings varies temporally. Physical and biologicalprocesses interact with anthropogenic activities to control the delivery of water and sediments aswell as rates of biogeochemical processes. Cloern & Jassby (2012) identified six primary driversof processes in coastal-estuarine systems: water consumption and diversion, human modificationof sediment supply, introduction of nonnative species, sewage input, environmental policy, andclimate shifts. The strength of these drivers and their interactions vary across estuaries, making itdifficult to identify universal trends across systems.

410 Canuel · Hardison

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Fluvial energy

Marine Corg

River Estuary Coastal ocean

Phytoplankton

MTZ

Resuspension,sorption/desorption,and decomposition

Tides and waves

hν photo-oxidation

DOC

Consumers

Sinking

Terrigenous POCTerrigenous DOC

CO2 CO2 CO2 CO2

Estuarine Corg

Decomposition

Terrigenous Corg

Light

Lateral exchangebetween wetlands

and shallowregions

Figure 1Sites of organic matter sources and exchange along the river–estuary–coastal ocean salinity gradient. The dominant sources of energy atthe river (fluvial) and ocean (tides and waves) end members are shown. A variety of abiotic (e.g., photochemical oxidation,sorption/desorption, sinking, and burial) and biotic (e.g., microbial decomposition, phytoplankton production, production in photicshallow environments, and uptake into consumer organisms) processes influence the fate of organic matter. Abbreviations: Corg,organic carbon; DOC, dissolved organic carbon; MTZ, maximum turbidity zone; POC, particulate organic carbon.

Freshwater discharge in rivers in temperate zones generally peaks from March through May,reflecting fluxes caused by spring thaw, whereas discharge is generally delayed in the northerntemperate and polar zones, reaching its peak from June through August owing to later snowmelt(Green et al. 2004). Even in relatively limited geographic regions, such as the northeast coastof the United States, estuaries exhibit tremendous variation resulting from differences in geol-ogy, sediment supply, land use, and development (Roman et al. 2000). In addition, estuaries varyin residence time, a key system determinant of OM composition and processing (Middelburg& Herman 2007). In a study of nine estuaries along a latitudinal gradient in western Europe,Middelburg & Herman (2007) showed that tidal estuaries tend to be characterized by high con-centrations of suspended particulate matter and long residence times, whereas river-dominatedestuaries usually have lower concentrations of suspended particulate matter and shorter residencetimes. In estuaries with long residence times, OM may undergo repeated cycles of resuspension andrepartitioning between dissolved and particulate phases (Aller 1998, Komada & Reimers 2001),promoting OM degradation and transformation (Figure 1). These recurring cycles of depositionand erosion influence the metabolic status of estuaries (e.g., whether they are net autotrophic ornet heterotrophic).

ORGANIC MATTER COMPOSITION: FROM ELEMENTALANALYSES TO BIOMARKERS

The coastal ocean comprises discrete but highly connected ecosystems, including rivers, estuaries,wetlands, and the continental shelf. One of the challenges of characterizing OM within this com-plex mosaic of subhabitats is the diverse range of sources from which OM derives (e.g., microalgaeand autochthonous organisms, tidal freshwater and salt marshes, terrigenous materials such as

www.annualreviews.org • Organic Matter in Estuaries 411

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Table 1 Biochemical composition of representative sources of organic matter in estuaries

Source Polysaccharidesa Proteins Lipids Nucleic acids Ligninb

Archaea Isoprenoid hydrocarbonsIsopranyl glycerol ether–linkedlipids

GDGT lipids

�8 = 0

Bacteriac 3–10% carbon<20 mg TCH2O/100 mg Corg

>15% riboseb

55–70% carbonD-Amino acidsPeptidoglycans

5–20% carbonIso- and anteiso-branched FAsPLFAsGDGT lipids

20% carbon �8 = 0

Microalgaec 5–50% carbon<20 mg TCH2O/100 mg Corg

25–50% carbon 5–20% carbon 20% carbon �8 = 0

Fungi Ergosterol �8 = 0Crustaceac 3–5% carbon

<10 mg TCH2O/100 mg Corg

45–70% carbon 5–20% carbonCholest-5-en-3β-ol(cholesterol)

20% carbon �8 = 0

Vascular plantsc 37–55% carbon>50 mg TCH2O/100 mg Corg

<2% riboseb

2–5% carbon <3% carbonLong-chain FAs (C24–C32)C29 sterols (β-sitosterol,stigmasterol)

n-Alkanes (C25–C35+) with astrong odd-carbon-numberpredominance

<1% carbon 15–40%carbon

�8 > 1

Angiosperms >20% xyloseb

<30% mannoseb

S/V > 1

Gymnosperms <20% xyloseb

>40% mannoseb

S/V = 0

Wood 40–80% carbon <1% carbon <3% carbon <1% carbon 15–40%carbon

Abbreviations: Corg, total organic carbon; FA, fatty acid; GDGT, glycerol dialkyl glycerol tetraether; PLFA, phospholipid-linked fatty acid; S, syringyl;TCH2O, total carbohydrate; V, vanillyl.aPolysaccharides include neutral, basic, and acidic sugars. The percent abundance of carbohydrate monomers is expressed on a glucose-free basis, as notedwith a “b” subscript (Cowie & Hedges 1984).bLambda (�) is defined as the sum of vanillyl, syringyl, and cinnamyl phenols normalized to 100 mg Corg (see Hedges & Mann 1979).cBiochemical composition of organisms from Whitehead (2008).

Dissolved organicmatter (DOM):the fraction of organicmatter that is dissolvedin water, typicallydefined as organiccompounds that passthrough a filter with a0.45-μm pore size

plant detritus and soils, and agricultural and urban runoff ) (Canuel 2001, Hedges & Keil 1999).Although OM from these sources differs in biochemical composition to some extent, overlappingsignatures between some sources (e.g., between marsh macrophytes and seagrasses, and betweenbenthic microalgae and phytoplankton) contribute to the challenge of OM source characteriza-tion (Table 1). Additionally, estuaries are highly dynamic, and the primary biological and physicaldrivers vary from hours to weeks to annual and multidecadal timescales, which means that short-term spot samplings may not represent the average composition of OM in these environments.An additional challenge is that creating a holistic picture of OM composition in estuaries requiresanalyzing both dissolved and particulate OM fractions [DOM (<0.45 μm) and POM (≥0.45 μm),respectively], but sampling methods and the detection limits of some analytes can make it difficultto apply geochemical tools equally to both phases.


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Particulate organicmatter (POM):the fraction of organicmatter that is retainedon a filter with a0.45-μm pore size

Biomarker: anorganic compound inwater, soils, sediments,rocks, coal, orpetroleum that can belinked to moleculessynthesized by livingorganisms

Compound-specificisotope analysis(CSIA): an analyticalmethod that measuresthe ratios of naturallyoccurring stableisotopes of elements inorganic compounds

Early studies of estuarine OM were based on bulk proxies such as atomic ratios of carbonto nitrogen (C:Na) and stable isotopes of carbon and nitrogen (δ13C and δ15N). These analysesare useful for distinguishing between marine and terrigenous OM in simple, two-end-membersystems, but OM sources in estuaries are more complex and often have overlapping values(Cloern et al. 2002). Subsequent studies examined bulk proxies (e.g., C:Na, δ13C, and �14C)across different size fractions and biochemical classes, providing insights about turnover ratesfor different pools of OM (Guo & Santschi 1997, Loh et al. 2006). Nuclear magnetic resonance(NMR) spectroscopy can provide complementary information. NMR offers insights about thefunctional group composition of OM and can be a powerful analytical tool, particularly when usedin combination with stable isotopes, biochemical class composition, and organic biomarkers (fora review, see Bianchi & Canuel 2011). Proton (1H) and 13C-NMR are the most common NMRanalyses and offer nondestructive approaches for characterizing functional groups in complexbiopolymers in estuarine ecosystems. 13C-NMR has been used to examine OM composition andtransformation along a salinity gradient. Abdulla et al. (2010) showed that high-molecular-weight(HMW) DOM collected along a transect in the Elizabeth River–Chesapeake Bay system con-sisted of three components (heteropolysaccharides, carboxyl-rich compounds, and amides/aminosugars) with different biogeochemical reactivities.

Biomarker compounds provide an additional level of detail in describing OM composition.Organic biomarkers were first applied to estuaries beginning in the late 1980s (Canuel et al. 1995,Saliot et al. 1988, Sicre et al. 1994), increasing the ability to distinguish among sources of OM inthese systems. Biomarkers take advantage of the unique biochemical classes that make up differentliving organisms as well as the geochemical stability of particular biochemicals in the environment(Figure 2, Table 1). Many biomarker studies in estuaries have focused on applying lipid andlignin biomarkers because unique compounds within these biochemical classes can be linked tospecific sources. By contrast, other biochemical classes, such as carbohydrates and proteins, consistof the same monomers across a wide range of sources. Over recent decades, the application ofbiomarkers to estuarine systems has increased dramatically, and the combination of biomarkersand stable isotopes has contributed substantially to our ability to distinguish among OM sourcesin estuaries (Canuel 2001, Hedges & Keil 1999, Jaff e et al. 2001). Biomarkers, used alone or incombination with bulk proxies, provide a more complete picture of estuarine OM compositionand have increased our ability to identify gradients in OM composition along the river–estuary–coastal ocean continuum. Compound-specific isotope analysis (CSIA) has further advanced ourunderstanding of OM sources through use of stable isotopes (δ13C and δ15N) and radiocarbon(�14C) isotopic values. In addition to providing source information, CSIA has led to insightsabout the sources of OM supporting microbial food webs (Coffin et al. 1990, Kelley et al. 1998,McCallister et al. 2004) and about OM sources and cycling during transport from the watershedto the coastal ocean (McIntosh et al. 2015).

BIOMARKER TOOLS FOR DIFFERENT ORGANIC MATTER PHASES

Because biomarkers differ in their affinity for dissolved and particulate matter owing to theirphysical properties (e.g., hydrophobicity and octanol-water partition coefficients), their usefulnessfor tracing OM sources across different phases varies. The initial application of lignin phenols,for example, was to plant, soil, and sediment samples (Hedges & Mann 1979, Hedges & Parker1976), largely reflecting the historical origins of this method in the wood industry. Subsequently,these methods were extended to particulate samples with relatively high loads of OM (>10 mg)and larger sample sizes. As interest in the carbon cycle has expanded, the lignin biomarker methodhas been extended to other phases, such as HMW DOM (Mannino & Harvey 2000, Opsahl


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AlgaeDinosterolBrassicasterolC20,22 PUFAs

BacteriaBacteriohopanetetrolDiplopteneBranched FAs

Aquatic macrophytesβ-Sitosterol

C18 FAsPaq

C25+ n-alkane-2-ones

Soil and vegetationβ-SitosterolC24–C28 FAs

Lignin phenolsBranched GDGT lipids

Figure 2Examples of important sources of organic matter in estuaries and lipid biomarker compounds useful fortracing these inputs to estuarine systems. Abbreviations: FA, fatty acid; GDGT, glycerol dialkyl glyceroltetraether; PUFA, polyunsaturated fatty acid. Photos of the forest and marsh used with permission of DaveMalmquist, Virginia Institute of Marine Science; photo of microalgae used with permission of PaulRichardson, Virginia Institute of Marine Science; photo of pink microbial aggregates (berries) in a pond atLittle Sippewissett salt marsh, Massachusetts, used with permission of Ederson Jesus, Brazilian AgriculturalResearch Corporation.

& Benner 1997). However, because lignin is present at very low concentrations in DOM, themethod has required modification to accommodate preconcentration of samples by methods suchas solid phase extraction and ultrafiltration as well as methodologies that improve the sensitivityof the analyses. Despite these advances, the volume of sample needed for lignin analyses in DOMcontinues to be a limitation and precludes the ability to work in some environments and to extendthe method to some samples (e.g., sediment pore waters).

Lipid biomarkers have undergone a similar evolution in their application to DOM samples.Lipid biomarkers were first used in sediment geochemistry studies in the fields of petroleumand environmental contaminant geochemistry. As interest in the characterization and cycling ofDOM has increased, and with the advent of ultrafiltration methodology, lipid biomarker analyseshave been extended to HMW DOM (e.g., Harvey & Mannino 2001, Loh et al. 2006). However,similar to the use of lignin biomarkers, lipid analyses are limited by the low concentration oflipids in DOM and the need for large sample sizes. Additionally, interpretation of biomarkerdistributions across DOM and POM may be confounded by the chemical behavior of lipids. Forexample, low concentrations of long-chain fatty acids (FAs), a class of biomarkers useful for tracingterrigenous sources, in DOM may reflect the lack of solubility of these FAs rather than an absenceof terrigenous material in DOM.

Carbohydrates (sugars) constitute a significant fraction of both DOM and POM, but becauseall organisms are made up of similar assemblages of simple sugars, carbohydrate monomers havelimited utility as biomarkers. However, although the concentration of specific carbohydrates can-not shed light on OM sources per se, the relative abundance of simple sugars can be used todifferentiate between plankton and vascular plants as well as among different types of plant tis-sues (Cowie & Hedges 1984). Carbohydrates may also provide insights about OM sources whenused in combination with other classes of biomarkers, such as lipids and stable isotopes (Medeiroset al. 2012). Because carbohydrates make up a relatively large proportion of OM, this class of


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biochemicals is also useful in studies of OM cycling and turnover in coastal systems (Arnosti et al.2009, Ziervogel & Arnosti 2009). Oakes et al. (2010), for example, used 13C labeling to investigateturnover of carbohydrates in shallow, subtidal sediments in Readings Bay, Australia. This studydemonstrated the important role that carbohydrates play in mediating production and the tightcoupling of carbon cycling processes by benthic microalgae and heterotrophic bacteria.

Proteins are abundant in DOM and POM (Bianchi & Canuel 2011 and references therein).This class of biochemicals comprises 20 L-amino acids that are essential to all organisms. Therelative abundance of L-amino acids is comparatively consistent across organisms, limiting the useof individual amino acids as biomarkers (Cowie et al. 1992). However, D-amino acids are unique topeptidoglycan, a bacterial cell wall constituent, allowing compounds such as D-alanine to be usedas biomarkers for bacteria (Veuger et al. 2005). Amino acids have also been used to provide insightsabout carbon and nitrogen cycling, and proxies such as the degradation index have proved usefulfor assessing the diagenetic state of OM in coastal environments (Dauwe & Middelburg 1998).

Dissolved Organic Matter

The quantity and quality of DOM in coastal waters are controlled by seasonality in riverine load-ing and primary productivity, biotic and abiotic turnover and remineralization, and the extent ofmixing. DOM is a complex mixture of organic molecules that varies greatly in molecular weightand functionality, thus making it difficult to characterize DOM using traditional chemical tech-niques. Because traditional biomarkers generally constitute a small fraction of the total DOC andare limited in their application to DOM, new methodologies have evolved that allow source char-acterization of DOM along estuarine salinity gradients. One approach to identifying sources ofOM in DOM is to examine the optical properties of chromophoric dissolved OM (CDOM) usingfluorescence spectroscopy coupled with parallel factor analysis (PARAFAC). Fluorescence excita-tion emission matrix (EEM) spectroscopy coupled with PARAFAC has been successfully appliedto a wide array of coastal systems to identify terrestrial, marine, and anthropogenic componentsof DOM (Osburn & Stedmon 2011, Stedmon & Markager 2005, Tzortziou et al. 2011).

The optical properties of CDOM provide a useful tool for distinguishing among differentsources of DOM and determining its composition and reactivity (Blough & Del Vecchio 2002).In coastal waters, CDOM derives primarily from river runoff of humic substances from soils andvegetation, and with distance from land, CDOM becomes more reflective of biological processessuch as autotrophic productivity, zooplankton feeding, and bacterial decomposition. In coastalwaters, CDOM properties and EEM-PARAFAC have been used to establish linkages betweenfreshwater DOM concentrations and biogeochemistry and watershed land use ( Jaff e et al. 2008,Lu et al. 2014), elucidate exchange of DOM across the marsh-estuary interface (Clark et al. 2008,Tzortziou et al. 2011), trace carbon sources and mixing (Osburn & Stedmon 2011, Spencer et al.2007), and provide measures of DOM transformation and lability (Huguet et al. 2009). However,CDOM makes up only a fraction of total DOM, and fluorescence properties are not universalacross study systems (Stubbins et al. 2014).

In recent years, mass spectrometry has increased our ability to characterize DOM at the molec-ular level (Minor et al. 2014, Stubbins et al. 2014). Recent applications of mass spectrometry toDOM include high-performance liquid chromatography coupled online to a mass spectrometer(Liu et al. 2011, van Roosmalen et al. 2010) and Fourier transform ion cyclotron resonance massspectrometry (FT-ICR-MS) (Minor et al. 2014, Stubbins et al. 2014). Electrospray ionizationcoupled to FT-ICR-MS has been used, for example, to characterize polar compounds associatedwith DOM at the molecular level during transport within a subestuary of the lower ChesapeakeBay (Sleighter & Hatcher 2008). FT-ICR-MS and high-resolution mass spectrometry have also


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been used to characterize important sources of DOM to estuaries and coastal waters such asgroundwater (Longnecker & Kujawinski 2011) and atmospheric aerosols (Wozniak et al. 2008).Overall, these studies have contributed to a richer understanding of DOM composition and itstransformation along the freshwater–estuary–coastal ocean continuum. As analytical capabilitiesadvance, our ability to characterize the sources and transformation processes influencing DOMwill continue to expand.

Suspended Particulate Organic Matter and Sediments

A wide variety of lipid biomarkers have been used to identify the sources of OM in estuaries(Bianchi & Canuel 2011 and references therein). Lipid biomarkers offer many advantages, such assource specificity; compounds that range in geochemical stability, thus making them amenable touse in studies spanning timescales ranging from those of microbial processes to geological time;and the ability to examine a range of OM sources simultaneously (e.g., aquatic, terrigenous, andanthropogenic). Lipids are powerful biomarkers because, unlike other classes of biochemicals thatare made up of the same subunits, they are biosynthesized in unique ways by different classes oforganisms (for a review, see Bianchi & Canuel 2011). FAs in higher plants, for example, are typi-cally long-chain (C24–C32), saturated moieties, whereas polyunsaturated FAs (C16–C22) are typicalof microalgae (Figure 2). Sterols are another class of lipid biomarkers applied widely to estuarinesystems; higher plants are dominated by C29 sterols (e.g., β-sitosterol or 24-ethylcholest-5-en-3β-ol), whereas C27 and C28 sterols are more abundant in aquatic plants and animals [e.g., cholesterol(chlolest-5-en-3β-ol) in crustaceans and brassicasterol (24-methylcholest-5,22-dien-3β-ol) in mi-croalgae] (Volkman 1986) (Figure 2). Lipid applications are not limited to distinguishing amongOM sources; they also provide information about the processors of OM. Heterotrophic bacteria,for example, biosynthesize a range of unique compounds, including iso- and anteiso-FAs, iso-prenoid hydrocarbons, and hopanols. Overall, the lipid biomarker approach takes advantages ofthe unique biosynthetic pathways of different organisms and uses this information to gain insightsabout the dominant sources and cycling of OM (Figure 2).

In the water column, lipid biomarker studies have been used to investigate how OM sourcesvary along the estuarine salinity continuum (Harvey & Mannino 2001, Loh et al. 2006, McCallisteret al. 2006) and how OM composition varies in response to hydrologic forcings (Canuel 2001,Medeiros et al. 2012). Lipid biomarkers have also provided the ability to compare the sources anddiagenetic state of OM in dissolved and particulate pools (Loh et al. 2006, Mannino & Harvey 1999,McCallister et al. 2006). Given the shallow nature of estuarine systems and the strong benthic-pelagic coupling that characterizes these systems, surface sediments are an additional importantpool of organic carbon (Corg) in estuaries. As a result, lipid biomarkers have been used to examinethe source composition of surface sediments (Zimmerman & Canuel 2001). Lipid biomarkersare also a tool for assessing how OM composition has changed over time in response to humandisturbance. In Chesapeake Bay, for example, Zimmerman & Canuel (2000, 2002) used lipidsto document changes in eutrophication. Similar work has been done in other systems, includingPuget Sound (Brandenberger et al. 2008), Florida Bay (Xu et al. 2007), and estuaries in Brazil(Carreira et al. 2011).

Studies of POM and surface sediments reveal a general pattern of OM distribution alongestuarine salinity gradients, characterized by (a) a dominance of OM derived from terrigenoussources at the freshwater end member, (b) decreasing terrigenous contributions to OM withincreasing salinity, and (c) large contributions of autochthonous OM below the maximum turbidityzone, where light and nutrients are available. In the case of POM, the transition from a dominance


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of terrigenous sources to a dominance of autochthonous sources is often abrupt and typically occursat the estuarine turbidity maximum. DOM sources, by contrast, often follow the patterns predictedbased on conservative mixing. At this level, biomarker distributions are consistent with previousstudies using δ13C values and C:N ratios.

However, biomarkers also have the potential to provide a richer and more complete pictureof OM sources in estuaries. Unlike the open ocean, where phytoplankton are the dominant au-totrophs, a variety of primary producers contribute to the high rates of production that characterizeestuaries, including marsh plants and seagrass, phytoplankton, benthic microalgae, and macroal-gae. Biomarkers provide a tool for distinguishing between these autotrophs. Algae and vascularplants, for example, have n-alkane distributions that are distinct in chain length, but other sourcesof Corg have intermediate chain lengths or overlapping n-alkane signatures. Alkanes in terrestrialplants function as epicuticular leaf waxes (Bianchi & Canuel 2011 and references therein) andare biosynthesized by decarboxylation of even-numbered long-chain carboxylic acids, resultingin n-alkanes with a strong odd-over-even preference that peaks around C27 or C29 (Bianchi &Canuel 2011 and references therein). By contrast, algae are characterized by shorter chain lengthsand lack a strong odd-over-even preference. Intermediate to these sources, coastal macrophytesare characterized by mid-chain-length n-alkanes with an odd-over-even chain-length preference(C23–C29) (Canuel et al. 1997, Ficken et al. 2000). Similarly, aquatic macrophytes are characterizedby mid-chain-length even-numbered FAs (e.g., C18 FAs) (Canuel et al. 1997).

Biomarker indices have been developed to identify sources of OM in environments character-ized by complex sources. One proxy, Paq, provides the ability to differentiate submerged/floatingaquatic macrophytes from emergent and terrestrial plant sources. Paq is an index of the relativeproportion of macrophyte sources based on the ratio of mid-chain-length n-alkanes (C23 and C25),which are derived from aquatic macrophytes, to long-chain-length homologs (C29 and C31), whichare characteristic of emergent plants (Ficken et al. 2000). This ratio has been extended to othercoastal systems, including the Hauraki Gulf in New Zealand (Pmar-aq) (Sikes et al. 2009). Pmar-aq

values of <0.1 indicate terrestrial plant sources, whereas values of 0.1–0.4 are characteristic ofemergent macrophytes, and values of 0.4–1.0 signify submerged/floating macrophytes (Fickenet al. 2000). A second proxy that has been widely applied to differentiate between aquatic andterrigenous sources in estuarine and coastal systems is the terrestrial-to-aquatic ratio (Meyers1997); this measure can be applied to both FA and hydrocarbon biomarkers and reflects the ratioof long-chain biomarkers (which represent terrigenous sources of OM) to short-chain biomarkers(which reflect aquatic sources).

An ongoing challenge in the application of biomarkers is to develop tools that allow differ-entiation among aquatic macrophytes, such as marsh and mangrove plants. One class of lipidbiomarkers, the n-alkane-2-ones, has proved useful for this purpose. A study in a South Floridaestuary demonstrated that seagrasses were the likely source of C25 n-alkane-2-ones, whereas theC27+ homologs were derived mainly from mangroves and freshwater marsh vegetation (Hernandezet al. 2001). Sources of carbon derived from mangroves have also been identified using taraxeroland other triterpenoid biomarkers, either alone or in combination with pollen studies (e.g., Kochet al. 2003, Versteegh et al. 2004).

Lignin is another class of biomarkers that has been widely applied to estuarine systems. Ligninis a class of biopolymers (600–1,000 kDa in size) that function as structural components in the cellwalls of vascular plants. It is typically analyzed by cupric oxide (CuO) catalyzed combustion andtetramethylammonium hydroxide (TMAH) thermochemolysis methods (Hatcher et al. 1995), andthe resulting phenols provide insights about contributions of vascular plant material to total Corg

(Goni & Hedges 1995, Hedges & Mann 1979). Lambda-8 (�8) is defined as the sum of vanillyl,


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syringyl, and cinnamyl phenols normalized to 100 mg Corg, and sigma-8 (�8) is defined as theconcentration of these phenols relative to the dry weight of the sample. In addition to providinga measure of the amount of OM derived from vascular plants, lignin also provides informationabout the type of plant tissue and its degradative state. The ratio of syringyl to vanillyl phenolscan be used to distinguish between angiosperm and gymnosperm plant tissues (Table 1), and theratio of cinnamyl to vanillyl phenols can be used to differentiate between hard plant tissues (e.g.,bark) and soft plant tissues (e.g., leaves). The acid/aldehyde ratio for vanillyl phenols, the ratio of3,5-dihydroxybenzoic acid to vanillyl phenols, and the ratio of p-hydroxyl phenols to the sum ofsyringyl and vanillyl phenols are three indices used to characterize the degradation/humificationstate of lignin (Houel et al. 2006, Louchouarn et al. 1999).

Concentrations of lignin associated with POM generally decrease along gradients from low-salinity regions to the mouths of estuarine systems (Bianchi & Argyrou 1997, Goni & Thomas2000). Soil and sediment samples collected from a forest–brackish marsh–salt marsh gradient ina southeastern US estuary (North Inlet) showed that woody and nonwoody gymnosperm andangiosperm sources dominated sedimentary OM at the forest site, whereas nonwoody marshplants (Spartina and Juncus) dominated at the marsh sites (Goni & Thomas 2000). Lignin wasmost degraded at the forest site and least degraded at the salt marsh site, where the occurrenceof anoxic conditions dominated. Although lignin is more abundant in POM and sediments, it hasalso been used to identify OM sources associated with HMW DOM. Similar to POM, ligninconcentrations associated with HMW DOM are generally higher in riverine and low-salinityregions and decrease with increasing salinity (Benner & Opsahl 2001). Processes thought toinfluence the abundance of lignin in HMW DOM in estuarine and coastal systems include lossesfrom bacterial decomposition, flocculation, sorption and desorption processes with resuspendedsediments (Guo & Santschi 2000, Mannino & Harvey 2000, Mitra et al. 2000), and photochemicalbreakdown (Benner & Opsahl 2001, Opsahl & Benner 1997). HMW DOM in bottom waters of theMiddle Atlantic Bight, for example, was found to be old and rich in lignin, which was attributed todesorption from sedimentary particulate matter derived from Chesapeake Bay and other estuariesalong the northeastern margin of the United States (Guo & Santschi 2000, Mitra et al. 2000).

Specific groups of glycerol dialkyl glycerol tetraether (GDGT) lipids are another proxy forterrigenous OM input to coastal settings (Hopmans et al. 2004). GDGTs are a recently discoveredgroup of membrane lipids synthesized by certain archaea and bacteria (for a review, see Schoutenet al. 2013). They are present in the membrane as GDGT core lipids with intact polar headgroups and have been found in a wide range of environments, including oceans and lakes and theirsediments as well as terrestrial soils (Hopmans et al. 2004, Kim et al. 2012). Branched GDGTs,a specific structural group with branched carbon skeletons, tend to be associated with terrestrialenvironments, specifically soil and peat. A recent literature review of the major GDGT corelipids in present-day environments revealed a dominance of branched GDGTs in coastal marinesediments, indicating the importance of soil OM to coastal sediments (Schouten et al. 2013).Similar findings led Hopmans et al. (2004) to develop the branched and isoprenoid tetraether(BIT) index based on the relative abundances of soil-derived branched GDGTs and crenarchaeol,the characteristic membrane lipid of the Thaumarchaea, which are found ubiquitously in marineand lacustrine environments (Schouten et al. 2013). The BIT index ranges from 0 (open marine) to1 (soils) and reflects the relative inputs of soil and marine OM sources, but not terrestrial vegetationinputs because vegetation does not contain branched GDGTs (Walsh et al. 2008). This differsgenerally from other terrestrial organic proxies, such as δ13Corg, C:N, odd-carbon-numbered n-alkanes, and lignin phenols, which reflect both soil OM and vegetation sources (Walsh et al. 2008,Weijers et al. 2009).


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ISOTOPIC DETERMINATION OF SOURCES AND AGESOF ORGANIC MATTER IN ESTUARIES

Stable Isotope Use

Carbon, nitrogen, and sulfur stable isotopes (δ13C, δ15N, and δ34S) have been used to distinguishterrestrial from aquatic OM as well as sewage and nutrient inputs; however, overlap in molecularor isotopic signatures of sources often produces ambiguous results (for a review, see Bianchi& Canuel 2011). CSIA provides an additional way to discriminate among multiple sourcesof OM (Ahad et al. 2011, Bianchi et al. 2004, Canuel et al. 1997). δ13C values for total Corg

represent the average of thousands (or more) of individual compounds that exhibit a range ofisotopic signatures. For example, polysaccharides and proteins are more 13C enriched than lipidsbecause of differences in biosynthesis (Hayes 2001). Selective degradation by microbes of specificfractions of OM may alter the bulk isotopic signature, making source tracking using bulk poolsless successful than biomarker approaches. Measuring the isotopic content of a biochemicalclass (e.g., proteins, carbohydrates, lipids, or lignin oxidation products) or a specific compoundcan be a powerful tracer of OM source, particularly when several organisms with isotopicallydistinct signatures synthesize the compound(s). For example, marsh plants are dominated bymid-chain-length n-alkanes, and their δ13C values are higher than those of phytoplankton andterrigenous plants and are unaltered during microbial degradation, thus providing a reliabletracer of marsh OM in estuaries (Ahad et al. 2011, Canuel et al. 1997). A multiproxy approachcombining carbon isotopic analysis of POC, lipids, and plant pigments in Texas estuaries provedeffective in determining that POC derived from phytoplankton rather than terrestrial inputs(Qian et al. 1996). The lipid and pigment δ13C signatures were on average 2–4� more depletedthan those of suspended POM, more accurately reflecting input from phytoplankton sources.

Stable isotopes can also be used to understand trophic structure and energy and matter flows infood webs, including microbial decomposition of OM (for a review, see Middelburg 2014). Recentdevelopments in CSIA of microbial biomarkers have allowed studies of OM processing within themicrobial compartment (Boschker & Middelburg 2002, Bouillon & Boschker 2006, Middelburget al. 2000). δ13C analysis of individual phospholipid-linked fatty acids (PLFAs) is commonlyused for this application. PLFAs are membrane lipids in microbes, and because these compoundsturn over relatively quickly following cell death, they are thought to represent viable or recentlyviable microbes. This approach allows isotopic separation of microbes and detritus, which hasaided in deciphering contributions from different microalgae groups (e.g., diatoms, green algae,and cyanobacteria) and bacteria to the diets of organisms such as estuarine zooplankton (Pelet al. 2003, van den Meersche et al. 2009) and sediment meio- and macrofauna (Evrard et al.2012). This approach has also revealed the carbon substrates supporting bacterial production inshallow coastal settings (Bouillon & Boschker 2006, Bouillon et al. 2011). A cross-system analysisof bacterial carbon sources in coastal sediments revealed high spatial variability in the δ13C ofbacterial PLFAs, reflecting a range of autochthonous sources, which did not always track thebulk sediment δ13C values for total Corg (Bouillon & Boschker 2006). In many cases during thisstudy, bacteria selectively degraded more labile carbon sources, such as benthic microalgae andphytodetritus, rather than relying on less labile macrophyte tissue. CSIA has also been combinedwith δD and δ15N (Caraco et al. 2010, Sachs & Schwab 2011). For example, δ15N analysis ofamino acids in zooplankton revealed that some amino acids become more enriched per trophictransfer than others, making them a more accurate tracer of trophic level for zooplankton andother consumers than δ15N analysis of bulk tissues alone (Chikaraishi et al. 2009, McClelland& Montoya 2002). CSIA may also be useful in identifying specific microbial processes, such asmethanotrophy (Hinrichs et al. 1999).


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Stable isotope studies are constrained by the natural variation in isotopic signatures of OMsources, which often overlap in estuarine systems. An alternative approach is deliberate addition ofisotopic tracers and subsequent tracking into bulk pools such as POC and/or individual biomarkers.This is a powerful tool in microbial ecology because it provides the possibility of directly linkingmicrobial identity (biomarker), biomass (concentration of the biomarker), and activity (isotopeassimilation) (Boschker & Middelburg 2002). Tracers (13C or 15N) can be introduced in organic orinorganic forms and as particulate or dissolved phases. Stable isotope labeling of algae, macrophytelitter, and DOM has been used to study the microbial decomposition of different substrates and theassimilation and uptake of POM by consumers. For example, a study of the uptake of 13C-labeledalgal exudates into bacterial PLFAs in Mediterranean coastal waters revealed that the majorityof bacterial carbon incorporation came from phytoplankton exudates under bloom conditions,whereas bacteria relied on alternative sources of carbon (e.g., viral lysis or sloppy feeding) tosupport production under conditions of high grazing pressure on phytoplankton (Fouilland et al.2014).

Additional studies using 13C- and 15N-labeling techniques have characterized the communitiesof bacteria involved in specific processes (Evershed et al. 2006, Knief et al. 2003) and have enabledthe inclusion of bacteria in food web studies (Boschker & Middelburg 2002, van den Meerscheet al. 2011). For example, studies tracing the uptake of 13C-bicarbonate into PLFAs have alloweddetection of active primary producers, such as microalgae and chemoautotrophic bacteria, inestuarine waters (Boschker & Middelburg 2002) and sediments (Evrard et al. 2008, Hardisonet al. 2011, Middelburg et al. 2000). Subsequent transfer of fixed 13C to heterotrophic organismscan then be followed by isotopic analysis of bacterial PLFAs and/or grazers (Hardison et al.2011, van Oevelen et al. 2006, Veuger et al. 2007). Recent analytical advances have allowed easierand more reliable isotopic analyses of a wide range of compound classes, such as carbohydratesand amino acids, via high-performance liquid chromatography coupled to an isotope-ratio massspectrometer (Boschker et al. 2008). This technique has been successfully applied to studies oftrophic transfer and processing of carbohydrates in sediment microbial communities, highlightingthe role of dissolved extracellular polymeric substances as a vehicle for direct carbon transferbetween microalgae and bacteria in shallow coastal sediments (Moerdijk-Poortvliet et al. 2014,Oakes et al. 2010). Additional advances have allowed investigators to trace 13C incorporation intoarchaeal biomarkers, providing opportunities to assess the role of archaea in OM decomposition.Lengger et al. (2014) conducted a decomposition study using 13C-labeled Corg and were unable todetect significant 13C-label incorporation in Thaumarchaea-derived intact polar lipids (GDGTs),whereas bacteria assimilated and respired the added Corg, indicating that these archaea were notimportant in processing labile Corg in Iceland shelf sediments.

Radiocarbon Isotope Use

Natural radiocarbon (�14C) is a useful tool for identifying the sources and ages of carbon and itsincorporation into estuarine food webs. Radiocarbon is often used in combination with δ13C, andtogether, these tools have provided many insights about carbon sources (for reviews, see Bauer& Bianchi 2011, Bianchi & Bauer 2011, Raymond & Bauer 2001). Radiocarbon has been usedto provide age and residence-time information about carbon pools (DOC, POC, and dissolvedinorganic carbon), to discern the ages of different biochemical classes, and to provide source andage information when combined with organic biomarkers (Loh et al. 2006, McCallister et al.2004, Wang et al. 2006). Recently, McIntosh et al. (2015) applied CSIA of lipid biomarkers toelucidate OM sources and their changing age distribution in the Delaware Estuary. These studieshave revealed a range in ages across different carbon pools and biochemical classes as well as


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Compound-specificradiocarbon analysis(CSRA): an analyticalmethod that measuresthe radiocarbon (14C)content of organiccompounds

between estuaries, providing insights about the carbon cycle and the residence times of differentcomponents.

In addition to using radiocarbon to measure the average age of total Corg pools in estuaries,several studies have investigated the radiocarbon ages of different biochemical classes. The resultsshowed that the total carbohydrate (TCH2O) and total hydrolyzable amino acid (THAA) poolsare typically younger in average 14C age, signifying that they reflect recently fixed carbon, whereasthe total lipid extract (TLE) pool tends to have more negative values, suggesting that it derivedfrom older carbon sources (Table 2). Loh et al. (2006) investigated the �14C ages of operationallydefined biochemical classes of ultrafiltered DOM and suspended POM in the Chesapeake Bay.In the low-salinity region (the Susquehanna River), the �14C age for TCH2O associated withHMW DOM was 1,468 years before present (BP, denoting years before 1950) during low flowand 762 years BP during high flow, whereas the �14C age for TLE was 5,354 years BP during highflow (Table 2). In high-salinity waters of Chesapeake Bay, the TCH2O had a modern (post-1950)�14C age, whereas the TLE was highly aged (6,866 years BP). The patterns of 14C age acrossdifferent biochemical classes associated with HMW DOM in Chesapeake Bay are also consistentwith what has been observed in other estuaries. In a study of 14C ages of biochemical classes acrossestuarine systems, Wang et al. (2006) also observed a wide range in 14C values associated withdifferent biochemical classes across study systems, and found a general trend showing that theaverage 14C ages of THAA and TCH2O were less (213 years BP and 254 years BP, respectively)than the average 14C age of TLE (13,414 years BP) (Table 2).

Radiocarbon has also been used to investigate the sources and ages of OM supportingestuarine food webs. Bacterial nucleic acids collected from Santa Rosa Sound, Florida, wereenriched in radiocarbon relative to bulk DOC and similar to atmospheric CO2, indicating thatbacteria within this system assimilated estuarine OM that was recently fixed (i.e., modern inage) (Cherrier et al. 1999). In the York River estuary in Virginia, the sources of OM supportingbacterial production varied along the estuary. The 14C values of bacterial nucleic acids weremost positive (i.e., youngest) at the freshwater end member of the York River (214 ± 29�) andbecame more negative (i.e., older) with increasing salinity, averaging 62 ± 20� and 15 ± 43�for the midsalinity and mouth locations, respectively (McCallister et al. 2004) (Table 2). Bacterialproduction in the Hudson River estuary in New York was supported by an even greater portion(up to 25%) of old (∼24,000 years BP) allochthonous OM. McCallister et al. (2004) hypothesizedthat this OM derived from soils in the watershed. Subsequent studies have investigated whetheraged OM contributes to the diets of consumer organisms. Caraco et al. (2010) found that agedOM is an important component of the diet of zooplankton in the Hudson River estuary.

Radiocarbon analyses of PLFAs can provide information about the sources and ages of carbonthat are assimilated by microbes. Slater et al. (2005) and Wakeham et al. (2006) used 14C analysesof PLFAs to investigate whether microbes living in oil-contaminated sediments were assimilatingfossil carbon. Wild Harbor, in West Falmouth, Massachusetts, was the site of an oil spill in 1969.Slater et al. (2005) did not find evidence for assimilation of petroleum hydrocarbons into PLFAsin this study system, suggesting that sediment microbes were assimilating natural sediment OMbut may have been respiring fossil carbon. By contrast, Wakeham et al. (2006) found that bacterialPLFAs were depleted in 14C, indicating that petroleum-derived carbon was incorporated intobacterial membrane lipids in salt marsh sediments of southeast Georgia.

Recently, McIntosh et al. (2015) used compound-specific radiocarbon analysis (CSRA) to un-derstand the source and age distribution of FAs in the Delaware Estuary. The authors observedthat FAs derived from different sources differ in ages along the estuary. For example, the 14C agesof short-chain FAs (C12 and C14) of microbial origin were greatest in the Delaware River anddecreased downstream as the salinity increased. This pattern is similar to that observed for �14C


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Tab

le2

Isot

opic

valu

esof

diss

olve

dan

dpa

rtic

ulat

eor

gani

cm

atte

rin

estu

arie

s

DO

CH

MW

UD

OM

PO

MT

LE

UD

OM

TH

AA

UD

OM

TC

H2O

UD

OM

Nuc

leic

acid

s

Loc

atio

nδ

13C

�14

Cδ

13C

�14

Cδ

13C

�14

Cδ

13C

�14

Cδ

13C

�14

Cδ

13C

�14

Cδ

13C

�14

CR

efer

ence

(s)

Bos

ton

Har

bor

Out

erha

rbor

(S=

27.1

)

−23.

7−6

7(5

00)

−25.

7−8

80(1

7,00

0)−2

3.8

−43

(300

)−1

8.5

−51

(370

)W

ang

etal

.20

06

Savi

nH

illC

ove

(S=

26.0

)

−30.

1−1

29(1

,050

)−3

0.7

−299

(2,8

00)

−29.

6−1

9(1

00)

−19.

2−7

3(5

60)

Isla

nden

d(S

=28

.2)

−24.

2−1

68(1

,420

)−2

8.9

−648

(8,3

30)

−23.

6−3

9(2

70)

−19.

1−2

0(1

10)

Che

sape

ake

Bay

Susq

ue-

hann

aR

iver

(HF)

−27.

0−8

1(6

79)

−27.

510

8 (mod

)−2

5.6

−61

(mod

)−2

8−4

87(5

,354

)−2

5.0

16 (mod

)−2

3.9

−91

(762

)B

auer

&B

ianc

hi20

11,L

ohet

al.2

006,

Ray

mon

d&

Bau

er20

01

Susq

ue-

hann

aR

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(LF)

−27.

0−8

1(6

79)

−26.

04

(mod

)−2

8.0

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1−2

4.3

−167

(1,4

68)

Bay

mou

th(H

F)−2

3.7

−77

(644

)−2

1.8

41(m

od)

−23.

060 (m

od)

−27.

7−2

0.8

25 (mod

)−2

1.0

3(m

od)

Bay

mou

th(L

F)−2

3.7

−29

(236

)−2

1.5

37(m

od)

−21.

418 (m

od)

−28.

3−5

75(6

,866

)−2

1.2

39 (mod

)−2

1.8

17(m

od)

Nor

folk

Har

bor

(S=

20)

−24.

5−2

2(1

25)

−26.

2−8

2(6

35)

−22.

113 (m

od)

−19.

43

(mod

)W

ang

etal

.20

06

Del

awar

eB

ay

Del

awar

eR

iver

(S=

0.2)

−24.

8−2

1(1

20)

−29

−946

(23,

300)

−27.

134 (m

od)

−22.

123

(mod

)W

ang

etal

.20

06

Hud

son

Riv

er

Fres

hwat

er(S

=0,

240

km)

−27.

0to

−27.

2−7

3to

−137

−29

−101

to+1

56−2

7.2

3M

cCal

liste

ret

al.2

004,

Ray

mon

d&

Bau

er20

01Fr

eshw

ater

(S=

0,12

2km

)

−27

−110

−27.

1−9

6−2

6.8

to−2

5.0

−153

to+1

6


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Stat

ion

A(S

=0)

−26.

636

−27.

3−1

66C

arac

oet

al.

2010

Stat

ion

G(S

=0)

−26.

451

−27.

0−1

15

Stat

ion

N(S

=0)

−28.

634

−26.

8−1

54

San

Die

goB

ay

Bay

mou

th(S

=33

.7)

−22.

5−1

77(1

,510

)−2

6.6

−872

(16,

450)

−24.

7−7

4(5

70)

−18.

5−2

3(1

25)

Wan

get

al.

2006

Cho

llas

Cre

ek(S

=33

.9)

−25.

1−2

05(1

,790

)−2

7.3

−774

(11,

900)

−23.

7−3

2(2

10)

−19.

7−3

2(2

05)

San

Fran

cisc

oB

ay

Hun

ters

Poi

nt(S

=28

.5)

−23.

1−1

00(7

95)

−29.

8−9

65(2

6,90

0)−2

1.7

−25

(150

)−1

9−7

3(5

60)

Wan

get

al.

2006

Sant

aR

osa

Soun

d

Sant

aR

osa

Soun

d(S

=18

)

−25.

722

−20.

912

0C

herr

ier

etal

.199

9

Yor

kR

iver

estu

ary

Fres

hwat

er(S

=0)

−28.

1to

−27.

843

4−3

0.0

to −28.

2

−190

to+2

4M

cCal

liste

ret

al.2

004,

Ray

mon

d&

Bau

er20

01

Mod

erat

e-sa

linity

wat

er(S

=10

)

−24.

5to

−24.

0−2

5.4

to−2

2.2

45to

91

Hig

h-sa

linity

wat

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for dissolved inorganic carbon, suggesting that the age of these FAs is controlled by the age ofinorganic carbon supporting microalgal production. By contrast, long-chain FAs (>C24) ascribedto terrigenous sources such as soils and higher plants increased in age with distance downstream,suggesting that aged terrigenous OM was delivered to downstream regions of the estuary.

Recent studies have noted the “aging” of Corg caused by anthropogenic disturbances such asdeforestation, increased agriculture, increased delivery of human wastewater, and hydrocarbonpollution (Butman et al. 2015, Griffith et al. 2009). Uptake of fossil fuel CO2 may also influencethe age of carbon in the coastal ocean (Bauer et al. 2013). Thus, changes in the ages of carbondelivered to coastal regions may represent an additional impact of anthropogenic activities, andfurther study is needed to investigate the implications of this for the coastal carbon cycle, foodwebs, and metabolism.

ESTUARIES AS HOT SPOTS OF ORGANIC MATTER PROCESSING

Studies have noted the importance of interfaces as hot spots for biogeochemical cycling (McClainet al. 2003). Estuaries are part of the integrated landscape of the coastal zone and interact with awide variety of environments that link land to sea, including tidal wetlands, rivers, and the conti-nental shelf. Along the flow path from land to the coastal ocean, materials are exchanged acrossa wide range of interfaces that interact over different timescales, including air-sea, river-estuary,groundwater-estuary, and water column–seabed (Figure 1). Exchanges across these different habi-tats and subenvironments contribute to the high levels of OM processing that characterize theseregions.

In contrast to the open ocean, which acts as a sink for atmospheric CO2, estuaries tend to be netheterotrophic and generally are sources of CO2 to the atmosphere (Cai 2011, Hopkinson & Smith2005). It is important to note, however, that although estuaries are net sources of CO2 on average,they may act as sinks at some times and locations. The efflux of CO2 from estuarine and coastalwaters results largely from high levels of heterotrophic activity associated with loadings of OMfrom allochthonous sources; nutrient enrichment that stimulates primary production and enhancesbacterial processing of OM; estuarine processes, such as priming, that promote the breakdownof refractory OM (Bianchi 2011); and the dynamic setting, which fosters transformations andremineralization of OM (Figures 1 and 3). Several distinguishing features of estuaries contributeto their role as efficient processors of OM, including (a) high rates of primary production, whichprovides a ready source of labile OM that then fuels heterotrophy; (b) a shallow water column,which allows light to penetrate and promotes photochemical alteration of OM (McCallister et al.2005, Smith & Benner 2005); (c) tight benthic-pelagic coupling, which enhances exchange ofmaterials such as labile OM, nutrients, and products of remineralization; and (d ) hydrologicinteractions between coastal aquifers and estuarine waters that supply dissolved nutrients andDOM (Fear et al. 2007, Longnecker & Kujawinski 2011, Rodellas et al. 2015).

Because estuaries are characterized by high spatial and temporal gradients in the amounts,forms, and quality of OM, remineralization processes are not equally distributed along the es-tuarine salinity gradient (Figure 1). Waters entering from rivers typically have high CO2 con-centrations, reflecting mineralization signatures from soils, freshwater wetlands, and resuspendedsediments in the upper estuary (Bianchi 2006 and references therein). Downstream of this re-gion is the estuarine turbidity maximum, or maximum turbidity zone, which represents one ofthe key locations of intense OM processing within estuaries (Figure 3). High concentrations ofsuspended particulate matter and repeated cycles of sedimentation and resuspension over diur-nal and neap-spring tidal cycles promote high rates of OM remineralization within these zones(Abril et al. 1999). This zone is also characterized by oscillating redox conditions and zones of


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CO2

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Figure 3Processes that influence the fate and cycling of organic matter within the maximum turbidity zone (MTZ) ofan estuary. The vertical dashed lines define the MTZ bioreactor zone, which begins near salinity ∼1 andextends into the higher-salinity region of the estuary. The geographical extent of the MTZ varies spatiallyand temporally in response to salinity, bottom topography, and tidal conditions. Abbreviations: DOM,dissolved organic matter; POM, particulate organic matter; SPM, suspended particulate matter.

oxygen depletion. For example, in the Gironde Estuary in France, labile DOC accumulates in theestuarine turbidity maximum (Abril et al. 1999), and co-metabolism is thought to promote thedecomposition of refractory POM, behaving similarly to the fluidized bed reactor described formobile muds associated with deltaic and continental shelf regions (Aller 1998). High concentra-tions of suspended particulate matter provide a high particle surface area and the opportunity totransform OM, nutrients, and reactive elements. Processes within this zone also enhance exchangeof materials between the dissolved and particulate phases that may promote biological and abiotic(e.g., photochemical) transformations of OM (Komada & Reimers 2001, Middelburg & Herman2007) (Figure 3). Downstream of the estuarine turbidity maximum, in the outer estuary and riverplume regions, light availability increases, often resulting in higher phytoplankton biomass. De-pending on levels of heterotrophic activity, these regions can be sources or sinks for atmosphericCO2. The Amazon plume region, for example, takes up atmospheric CO2 at levels comparable tothose of the river and wetland regions within this study system (Richey et al. 2002). Likewise, theMississippi River plume acts as a sink for CO2 (Cai 2003).

Considerable attention has been given to the shallow water column of estuaries and the tightcoupling between pelagic and benthic systems (Hopkinson 1987, Kelly et al. 1985). Water depthplays an important role in processes that shape estuaries, including light availability, resuspension,and feedbacks between nutrient cycling in the seabed and water column responses. Most studieshave focused on the deeper, main stem regions of estuaries; less attention has been given to thehighly productive shallow habitats at the perimeters of estuaries and lateral exchanges of nutrientsand OM from shallow to deep regions. This enhanced productivity results from the combinedeffects of high nutrient inputs and light penetration to the sediment surface in these shallowregions, which promote the growth of benthic primary producers (Duarte 1995). Macroalgae and


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benthic microalgae may be at least as important as phytoplankton in shallow environments interms of biomass and POC production (Cahoon 1999, Underwood & Kromkamp 1999, Websteret al. 2002). OM produced by benthic autotrophs may undergo decomposition or be respiredby benthic and pelagic bacterial communities (Banta et al. 2004; Hardison et al. 2010, 2011), beincorporated into benthic and pelagic food webs (Cebrian 2004, Hondula et al. 2014), be buried(Middelburg et al. 2004), or be exported. Fringing tidal fresh- and saltwater marshes and mangrovesare also major sources of Corg in estuarine systems (Kirby & Gosselink 1976, Pomeroy & Wiegert1981). Salt marshes may transport bioavailable OM laterally as far as nearshore continental shelfand slope waters, thereby enhancing secondary production (Bianchi & Argyrou 1997, Odum1968). Susceptibility to herbivory and decomposition varies across and within groups of benthicproducers, as both processes depend on the chemical composition, nutrient content, and carbonquality of the plant tissue. Generally, vascular plants such as marshes, mangroves, and seagrassesare enriched in carbon-rich ligneous and phenolic compounds that are considered more refractoryand require microbial breakdown to convert the more recalcitrant polymers to more labile Corg

available to consumers (Moran & Hodson 1989).

SUMMARY POINTS

1. Overall, estuaries play an important role in the carbon cycle as regions of organic matter(OM) production, cycling, and export to the coastal ocean.

2. The composition and abundance of OM in estuaries have been shaped and modified byhuman activities. These regions will continue to remain vulnerable to human pressuresowing to nutrient enrichment, sea level rise, and climate change.

3. Organic geochemical tools such as biomarkers, stable isotopes, and radiocarbon enableinvestigators to identify sources of OM in complex estuarine systems. These tools provideinsights about present systems as well as how these systems have evolved over time bothnaturally and in response to human activities.

4. Estuaries interact with a wide variety of environments along the land-ocean margin,including tidal wetlands, rivers, and the continental shelf. These interfaces (e.g., air-sea,river-estuary, groundwater-estuary, and water column–seabed interfaces) are hot spotsof biogeochemical cycling and promote high levels of OM processing.

5. Gaps in our understanding of OM composition at the land-ocean margin include(a) lateral exchange of OM and nutrients between environments that interact with estuar-ies (e.g., marshes, shallow regions such as tidal flats and seagrass beds, and the continentalshelf ); (b) relationships between OM composition, rates of microbial processes, and activemicrobial communities (e.g., identifying new microbes and their metabolic capabilitiesthrough genetics); and (c) the role of stochastic events such as storms in OM delivery andsubsequent biogeochemical responses to these events.

FUTURE ISSUES

1. Coastal nutrient enrichment and the ensuing eutrophication are increasing globallyand altering the dominant autotrophic communities. These changes will influence OMsources and cycling, including rates of primary production, grazing, decomposition, andnutrient cycling.


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2. Estuaries are highly vulnerable to climate change. Sea level rise, changes in precipitation,and a greater frequency of intense storm events will influence the delivery of freshwater,sediments, nutrients, and OM to estuaries and coastal waters. These changes will, inturn, influence important drivers of the coastal zone, such as stratification, light levels,and nutrient supply. Increased warming will likely increase rates of metabolism.

3. A remaining frontier in biogeochemistry is the ability to link chemical composition togenetic information to understand how OM quality and quantity regulate microbialcommunity structure and function along the land-ocean continuum.

4. OM characterization is highly dependent on analytical tools. Technological advances inmass spectrometry methods (e.g., Fourier transform ion cyclotron resonance mass spec-trometry, liquid chromatography–tandem mass spectrometry, and high-performance liq-uid chromatography coupled to isotope-ratio mass spectrometry) and compound-specificstable isotope and radiocarbon analyses show promise for enhancing our ability to char-acterize the sources and cycling of OM in complex coastal environments.

DISCLOSURE STATEMENT

The authors are not aware of any affiliations, memberships, funding, or financial holdings thatmight be perceived as affecting the objectivity of this review.

ACKNOWLEDGMENTS

We would like to dedicate this article to Dr. Cindy Lee, who provided the inspiration and impetusfor us to undertake this review. Her research career has provided a model for conducting col-laborative, interdisciplinary research, and she has been influential in developing new conceptualand analytical approaches fundamental to advancing the field of organic biogeochemistry. We ac-knowledge support from the National Science Foundation during preparation of this manuscript(OCE-0962277 to E.A.C., EAR-1417433 to A.K.H.) and the NASA Carbon Cycle Science pro-gram (NASA grant NNX14AP06G to E.A.C.). This review is Contribution 3500 of the VirginiaInstitute of Marine Science, The College of William & Mary, and Contribution 1708 of theUniversity of Texas Marine Science Institute.

LITERATURE CITED

Abdulla HAN, Minor EC, Hatcher PG. 2010. Using two-dimensional correlations of 13C NMR and FTIR toinvestigate changes in the chemical composition of dissolved organic matter along an estuarine transect.Environ. Sci. Technol. 44:8044–49

Abril G, Etcheber H, Le Hir P, Bassoullet P, Boutier B, Frankignoulle M. 1999. Oxic/anoxic oscillations andorganic carbon mineralization in an estuarine maximum turbidity zone (the Gironde, France). Limnol.Oceanogr. 44:1304–15

Ahad JME, Ganeshram RS, Bryant CL, Cisneros-Dozal LM, Ascough PL, et al. 2011. Sources of n-alkanes inan urbanized estuary: insights from molecular distributions and compound-specific stable and radiocarbonisotopes. Mar. Chem. 126:239–49

Aller RC. 1998. Mobile deltaic and continental shelf muds as suboxic, fluidized bed reactors. Mar. Chem.61:143–55

Arnosti C, Ziervogel K, Ocampo L, Ghobrial S. 2009. Enzyme activities in the water column and in shallowpermeable sediments from the northeastern Gulf of Mexico. Estuar. Coast. Shelf Sci. 84:202–8


Ann

u. R

ev. M

ar. S

ci. 2

016.

8:40

9-43

4. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

Acc

ess

prov

ided

by

Old

Dom

inio

n U

nive

rsity

on

02/2

6/18

. For

per

sona

l use

onl

y.


Banta GT, Pedersen MF, Nielsen SL. 2004. Decomposition of marine primary producers: Consequences fornutrient recycling and retention in coastal ecosystems. See Nielsen et al. 2004, pp. 187–216

Bauer JE, Bianchi TS. 2011. Dissolved organic carbon cycling and transformation. In Treatise on Estuarine andCoastal Science, Vol. 5: Biogeochemistry, ed. E Wolanski, DS McLusky, pp. 7–67. Waltham, MA: Academic

Bauer JE, Cai W-J, Raymond PA, Bianchi TS, Hopkinson CS, Regnier PAG. 2013. The changing carboncycle of the coastal ocean. Nature 504:61–70

Benner R, Opsahl S. 2001. Molecular indicators of the sources and transformations of dissolved organic matterin the Mississippi river plume. Org. Geochem. 32:597–611

Bianchi TS. 2006. Biogeochemistry of Estuaries. Oxford, UK: Oxford Univ. PressBianchi TS. 2011. The role of terrestrially derived organic carbon in the coastal ocean: a changing paradigm

and the priming effect. PNAS 108:19473–81Bianchi TS, Argyrou ME. 1997. Temporal and spatial dynamics of particulate organic carbon in the Lake

Pontchartrain estuary, southeast Louisiana, U.S.A. Estuar. Coast. Shelf Sci. 45:287–97Bianchi TS, Bauer JE. 2011. Particulate organic carbon cycling and transformation. In Treatise on Estuarine

and Coastal Science, Vol. 5: Biogeochemistry, ed. E Wolanski, DS McLusky, pp. 69–117. Waltham, MA:Academic

Bianchi TS, Canuel EA. 2011. Chemical Biomarkers in Aquatic Ecosystems. Princeton, NJ: Princeton Univ. PressBianchi TS, Filley T, Dria K, Hatcher PG. 2004. Temporal variability in sources of dissolved organic carbon

in the lower Mississippi River. Geochim. Cosmochim. Acta 68:959–67Blough NV, Del Vecchio R. 2002. Chromophoric DOM in the coastal environment. In Biogeochemistry of

Marine Dissolved Organic Matter, ed. DA Hansell, CA Carlson, pp. 509–45. San Diego, CA: AcademicBorges AV. 2005. Do we have enough pieces of the jigsaw to integrate CO2 fluxes in the coastal ocean?

Estuaries 28:3–27Boschker HTS, Middelburg JJ. 2002. Stable isotopes and biomarkers in microbial ecology. FEMS Microbiol.

Ecol. 40:85–95Boschker HTS, Moerdijk-Poortvliet TCW, van Breugel P, Houtekamer M, Middelburg JJ. 2008. A

versatile method for stable carbon isotope analysis of carbohydrates by high-performance liquidchromatography/isotope ratio mass spectrometry. Rapid Commun. Mass Spectrom. 22:3902–8

Bouillon S, Boschker HTS. 2006. Bacterial carbon sources in coastal sediments: a cross-system analysis basedon stable isotope data of biomarkers. Biogeosciences 3:175–85

Bouillon S, Gillikin DP, Connolly RM. 2011. Use of stable isotopes to understand food webs and ecosystemfunctioning in estuaries. In Treatise on Estuarine and Coastal Science, Vol. 7: Functioning of Ecosystems at theLand–Ocean Interface, ed. E Wolanski, DS McLusky, pp. 143–73. Waltham, MA: Academic

Brandenberger JM, Crecelius EA, Louchouarn P. 2008. Historical inputs and natural recovery rates for heavymetals and organic biomarkers in Puget Sound during the 20th century. Environ. Sci. Technol. 42:6786–90

Butman DE, Wilson HF, Barnes RT, Xenopoulos MA, Raymond PA. 2015. Increased mobilization of agedcarbon to rivers by human disturbance. Nat. Geosci. 8:112–16

Cahoon LB. 1999. The role of benthic microalgae in neritic ecosystems. Oceanogr. Mar. Biol. 37:47–86Cai W-J. 2003. Riverine inorganic carbon flux and rate of biological uptake in the Mississippi River plume.

Geophys. Res. Lett. 30:1032Cai W-J. 2011. Estuarine and coastal ocean carbon paradox: CO2 sinks or sites of terrestrial carbon incinera-

tion? Annu. Rev. Mar. Sci. 3:123–45Canuel EA. 2001. Relations between river flow, primary production and fatty acid composition of particulate

organic matter in San Francisco and Chesapeake Bays: a multivariate approach. Org. Geochem. 32:563–83Canuel EA, Cammer SS, McIntosh HA, Pondell CR. 2012. Climate change impacts on the organic carbon

cycle at the land-ocean interface. Annu. Rev. Earth Planet. Sci. 40:685–711Canuel EA, Cloern J, Ringelberg D, Guckert J, Rau G. 1995. Molecular and isotopic tracers used to examine

sources of organic matter and its incorporation into the food webs of San Francisco Bay. Limnol. Oceanogr.40:67–81

Canuel EA, Freeman KH, Wakeham SG. 1997. Isotopic compositions of lipid biomarker compounds inestuarine plants and surface sediments. Limnol. Oceanogr. 42:1570–83

Caraco N, Bauer JE, Cole JJ, Petsch S, Raymond P. 2010. Millennial-aged organic carbon subsidies to amodern river food web. Ecology 91:2385–93


Ann

u. R

ev. M

ar. S

ci. 2

016.

8:40

9-43

4. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

Acc

ess

prov

ided

by

Old

Dom

inio

n U

nive

rsity

on

02/2

6/18

. For

per

sona

l use

onl

y.


Carreira RS, Araujo MP, Costa TLF, Sporl G, Knoppers BA. 2011. Lipids in the sedimentary record asmarkers of the sources and deposition of organic matter in a tropical Brazilian estuarine-lagoon system.Mar. Chem. 127:1–11

Cebrian J. 2004. Grazing on benthic primary producers. See Nielsen et al. 2004, pp. 153–85Chen C-TA, Borges AV. 2009. Reconciling opposing views on carbon cycling in the coastal ocean: continental

shelves as sinks and near-shore ecosystems as sources of atmospheric CO2. Deep-Sea Res. II 56:578–90Cherrier J, Bauer JE, Druffel ERM, Coffin RB, Chanton JP. 1999. Radiocarbon in marine bacteria: evidence

for the ages of assimilated carbon. Limnol. Oceangr. 44:730–36Chikaraishi Y, Ogawa NO, Kashiyama Y, Takano Y, Suga H, et al. 2009. Determination of aquatic food-web

structure based on compound-specific nitrogen isotopic composition of amino acids. Limnol. Oceanogr.Methods 7:740–50

Clark CD, Litz LP, Grant SB. 2008. Salt marshes as a source of chromophoric dissolved organic matter(CDOM) to Southern California coastal waters. Limnol. Oceanogr. 53:1923–33

Cloern JE, Canuel EA, Harris D. 2002. Stable carbon and nitrogen isotope composition of aquatic andterrestrial plants of the San Francisco Bay estuarine system. Limnol. Oceanogr. 47:713–29

Cloern JE, Jassby AD. 2012. Drivers of change in estuarine-coastal ecosystems: discoveries from four decadesof study in San Francisco Bay. Rev. Geophys. 50:RG4001–33

Coffin RB, Velinsky DJ, Devereux R, Price WA, Cifuentes LA. 1990. Stable carbon isotope analysis of nucleicacids to trace sources of dissolved substrates used by estuarine bacteria. Appl. Environ. Microbiol. 56:2012–20

Cowie GL, Hedges JI. 1984. Carbohydrate sources in a coastal marine environment. Geochim. Cosmochim. Acta48:2075–87

Cowie GL, Hedges JI, Calvert SE. 1992. Sources and relative reactivities of amino acids, neutral sugars, andlignin in an intermittently anoxic marine environment. Geochim. Cosmochim. Acta 56:1963–78

Dauwe B, Middelburg JJ. 1998. Amino acids and hexosamines as indicators of organic matter degradationstate in North Sea sediments. Limnol. Oceanogr. 43:782–98

Diaz RJ, Rosenberg R. 2008. Spreading dead zones and consequences for marine ecosystems. Science 321:926–29

Duarte CM. 1995. Submerged aquatic vegetation in relation to different nutrient regimes. Ophelia 41:87–112Evershed RP, Crossman ZM, Bull ID, Mottram H, Dungait JAJ, et al. 2006. 13C-labelling of lipids to inves-

tigate microbial communities in the environment. Curr. Opin. Biotechnol. 17:72–82Evrard V, Cook PLM, Veuger B, Huettel M, Middelburg JJ. 2008. Tracing carbon and nitrogen incorporation

and pathways in the microbial community of a photic subtidal sand. Aquat. Microb. Ecol. 53:257–69Evrard V, Huettel M, Cook PLM, Soetaert K, Heip CHR, Middelburg JJ. 2012. Importance of phytodetritus

and microphytobenthos for heterotrophs in a shallow subtidal sandy sediment. Mar. Ecol. Prog. Ser.455:13–31

Fear JM, Paerl HW, Braddy JS. 2007. Importance of submarine groundwater discharge as a source of nutrientsfor the Neuse River Estuary, North Carolina. Estuaries Coasts 30:1027–33

Ficken KJ, Li B, Swain DL, Eglinton G. 2000. An n-alkane proxy for the sedimentary input of submerged/floating freshwater aquatic macrophytes. Org. Geochem. 31:745–49

Fouilland E, Tolosa I, Bonnet D, Bouvier C, Bouvier T, et al. 2014. Bacterial carbon dependence on freshlyproduced phytoplankton exudates under different nutrient availability and grazing pressure conditions incoastal marine waters. FEMS Microbiol. Ecol. 87:757–69

Goni MA, Hedges JI. 1995. Sources and reactivities of marine-derived organic matter in coastal sediments asdetermined by alkaline CuO oxidation. Geochim. Cosmochim. Acta 59:2965–81

Goni MA, Thomas KA. 2000. Sources and transformations of organic matter in surface soils and sedimentsfrom a tidal estuary (North Inlet, South Carolina, U.S.A.). Estuaries 23:548–64

Green P, Vorosmarty C, Meybeck M, Galloway J, Peterson B, Boyer E. 2004. Pre-industrial and contemporaryfluxes of nitrogen through rivers: a global assessment based on typology. Biogeochemistry 68:71–105

Griffith DR, Barnes RT, Raymond PA. 2009. Inputs of fossil carbon from wastewater treatment plants to U.S.rivers and oceans. Environ. Sci. Technol. 43:5647–51

Guo L, Santschi PH. 1997. Isotopic and elemental characterization of colloidal organic matter from theChesapeake Bay and Galveston Bay. Mar. Chem. 59:1–15


Ann

u. R

ev. M

ar. S

ci. 2

016.

8:40

9-43

4. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

Acc

ess

prov

ided

by

Old

Dom

inio

n U

nive

rsity

on

02/2

6/18

. For

per

sona

l use

onl

y.


Guo L, Santschi PH. 2000. Sedimentary sources of old high molecular weight dissolved organic carbon fromthe ocean margin benthic nepheloid layer. Geochim. Cosmochim. Acta 64:651–60

Hardison AK, Anderson IC, Canuel EA, Tobias CR, Veuger B. 2011. Carbon and nitrogen dynamics inshallow photic systems: interactions between macroalgae, microalgae, and bacteria. Limnol. Oceanogr.56:1489–503

Hardison AK, Canuel EA, Anderson IC, Veuger B. 2010. Fate of macroalgae in benthic systems: carbon andnitrogen cycling within the microbial community. Mar. Ecol. Prog. Ser. 414:41–55

Harvey HR, Mannino A. 2001. The chemical composition and cycling of particulate and macromoleculardissolved organic matter in temperate estuaries as revealed by molecular organic tracers. Org. Geochem.32:527–42

Hatcher PG, Nanny MA, Minard RD, Dible SC, Carson DM. 1995. Comparison of two thermochemolyticmethods for the analysis of lignin in decomposing gymnosperm wood: the CuO oxidation method and themethod of thermochemolysis with tetramethylammonium hydroxide (THAH). Org. Geochem. 23:881–88

Hayes JN. 2001. Fractionation of the isotopes of carbon and hydrogen in biosynthetic processes. In StableIsotope Geochemistry, ed. JW Valley, DR Cole, pp. 225–78. Rev. Mineral. Geochem. 43. Chantilly, VA:Mineral. Soc. Am.

Hedges JI, Keil RG. 1999. Organic geochemical perspectives on estuarine processes: sorption reactions andconsequences. Mar. Chem. 65:55–65

Hedges JI, Keil RG, Benner R. 1997. What happens to terrestrial organic matter in the ocean? Org. Geochem.27:195–212

Hedges JI, Mann DC. 1979. The characterization of plant tissues by their lignin oxidation products. Geochim.Cosmochim. Acta 43:1803–7

Hedges JI, Parker PL. 1976. Land-derived organic matter in surface sediments from the Gulf of Mexico.Geochim. Cosmochim. Acta 40:1019–29

Hermann M, Najjar RJ, Kemp WM, Alexander RB, Boyer EW, et al. 2015. Net ecosystem production andorganic carbon balance of U.S. East Coast estuaries: a synthesis approach. Glob. Biogeochem. Cycles 29:96–111

Hernandez ME, Mead R, Peralba MC, Jaff e R. 2001. Origin and transport of n-alkane-2-ones in a subtropicalestuary: potential biomarkers for seagrass-derived organic matter. Org. Geochem. 32:21–32

Hinrichs KU, Hayes JM, Sylva SP, Brewer PG, DeLong EF. 1999. Methane-consuming archaebacteria inmarine sediments. Nature 398:802–5

Hondula KL, Pace ML, Cole JJ, Batt RD. 2014. Hydrogen isotope discrimination in aquatic primary producers:implications for aquatic food web studies. Aquat. Sci. 76:217–29

Hopkinson CS. 1987. Nutrient regeneration in shallow-water sediments of the estuarine plume region of thenearshore Georgia Bight, USA. Mar. Biol. 94:127–42

Hopkinson CS Jr, Smith EM. 2005. Estuarine respiration: an overview of benthic, pelagic, and whole systemrespiration. In Respiration in Aquatic Ecosystems, ed. PA del Giorgio, PJLB Williams, pp. 122–46. Oxford,UK: Oxford Univ. Press

Hopmans EC, Weijers JWH, Schefuss E, Herfort L, Damste JSS, Schouten S. 2004. A novel proxy forterrestrial organic matter in sediments based on branched and isoprenoid tetraether lipids. Earth Planet.Sci. Lett. 224:107–16

Houel S, Louchouarn P, Lucotte M, Canuel R, Ghaleb B. 2006. Translocation of soil organic matter followingreservoir impoundment in boreal systems: implications for in situ production. Limnol. Oceanogr. 51:1497–513

Huguet A, Vacher L, Relexans S, Saubusse S, Froidefond JM, Parlanti E. 2009. Properties of fluorescentdissolved organic matter in the Gironde Estuary. Org. Geochem. 40:706–719

IPCC (Intergov. Panel Clim. Change). 2013. Summary for policymakers. In Climate Change 2013: The PhysicalScience Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel onClimate Change, ed. TF Stocker, D Qin, G-K Plattner, M Tignor, SK Allen, et al., pp. 3–29. Cambridge,UK: Cambridge Univ. Press

Jaffe R, McKnight D, Maie N, Cory R, McDowell WH, Campbell JL. 2008. Spatial and temporal variationsin DOM composition in ecosystems: the importance of long-term monitoring of optical properties.J. Geophys. Res. 113:G04032


Ann

u. R

ev. M

ar. S

ci. 2

016.

8:40

9-43

4. D

ownl

oade

d fr

om w

ww

.ann

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Acc

ess

prov

ided

by

Old

Dom

inio

n U

nive

rsity

on

02/2

6/18

. For

per

sona

l use

onl

y.


Jaffe R, Mead R, Hernandez ME, Peralba MC, DiGuida OA. 2001. Origin and transport of sedimentary organicmatter in two subtropical estuaries: a comparative, biomarker-based study. Org. Geochem. 32:507–26

Kelley CA, Coffin RB, Cifuentes LA. 1998. Stable isotope evidence for alternative bacterial carbon sources inthe Gulf of Mexico. Limnol. Oceanogr. 43:1962–69

Kelly JR, Berounsky VM, Nixon SW, Oviatt CA. 1985. Benthic-pelagic coupling and nutrient cycling acrossan experimental eutrophication gradient. Mar. Ecol. Prog. Ser. 26:207–19

Kim JH, Zell C, Moreira-Turcq P, Perez MAP, Abril G, et al. 2012. Tracing soil organic carbon in the lowerAmazon River and its tributaries using GDGT distributions and bulk organic matter properties. Geochim.Cosmochim. Acta 90:163–80

Kirby CJ, Gosselink JG. 1976. Primary production in a Louisiana Gulf Coast Spartina alterniflora marsh.Ecology 57:1052–59

Knief C, Altendorf K, Lipski A. 2003. Linking autotrophic activity in environmental samples with specificbacterial taxa by detection of 13C-labelled fatty acids. Environ. Microbiol. 5:1155–67

Koch BP, Rullkotter J, Lara RJ. 2003. Evaluation of triterpenols and sterols as organic matter biomarkers ina mangrove ecosystem in northern Brazil. Wetl. Ecol. Manag. 11:257–63

Komada T, Reimers CE. 2001. Resuspension-induced partitioning of organic carbon between solid and solu-tion phases from a river-ocean transition. Mar. Chem. 76:155–74

Lengger SK, Lipsewers YA, de Haas H, Damste JSS, Schouten S. 2014. Lack of 13C-label incorporationsuggests low turnover rates of thaumarchaeal intact polar tetraether lipids in sediments from the Icelandshelf. Biogeosciences 11:201–16

Liu Z, Sleighter RL, Zhong J, Hatcher PG. 2011. The chemical changes of DOM from black waters to coastalmarine waters by HPLC combined with ultrahigh resolution mass spectrometry. Estuar. Coast. Shelf Sci.92:205–16

Loh AN, Bauer JE, Canuel EA. 2006. Dissolved and particulate organic matter source-age characterization inthe upper and lower Chesapeake Bay: a combined isotope and biochemical approach. Limnol. Oceanogr.51:1421–31

Longnecker K, Kujawinski EB. 2011. Composition of dissolved organic matter in groundwater. Geochim.Cosmochim. Acta 75:2752–61

Lotze HK, Lenihan HS, Bourque BJ, Bradbury RH, Cooke RG, et al. 2006. Depletion, degradation, andrecovery potential of estuaries and coastal seas. Science 312:1806–9

Louchouarn P, Lucotte PM, Farella N. 1999. Historical and geographical variations of sources and transportof terrigenous organic matter within a large-scale coastal environment. Org. Geochem. 30:675–99

Lu Y, Bauer J, Canuel E, Chambers RM, Yamashita Y, et al. 2014. Effects of land use on sources and ages ofinorganic and organic carbon in temperate headwater streams. Biogeochemistry 119:275–92

Mannino A, Harvey HR. 1999. Lipid composition in particulate and dissolved organic matter in the DelawareEstuary: sources and diagenetic patterns. Geochim. Cosmochim. Acta 63:2219–35

Mannino A, Harvey HR. 2000. Terrigenous dissolved organic matter along an estuarine gradient and its fluxto the coastal ocean. Org. Geochem. 31:1611–25

McCallister SL, Bauer JE, Cherrier JE, Ducklow HW. 2004. Assessing sources and ages of organic mattersupporting river and estuarine bacterial production: a multiple-isotope (�14C, δ13C, δ15N) approach.Limnol. Oceanogr. 49:1687–702

McCallister SL, Bauer JE, Ducklow HW, Canuel EA. 2006. Sources of estuarine dissolved and particulateorganic matter: a multi-tracer approach. Org. Geochem. 37:454–68

McCallister SL, Bauer JE, Kelly J, Ducklow HW. 2005. Effects of sunlight on decomposition of estuarinedissolved organic C, N and P and bacterial metabolism. Aquat. Microb. Ecol. 40:25–35

McClain ME, Boyer EW, Dent CL, Gergel SE, Grimm NB, et al. 2003. Biogeochemical hot spots and hotmoments at the interface of terrestrial and aquatic ecosystems. Ecosystems 6:301–12

McClelland JW, Montoya JP. 2002. Trophic relationships and the nitrogen isotopic composition of aminoacids in plankton. Ecology 83:2173–80

McIntosh HA, McNichol AP, Xu L, Canuel EA. 2015. Source-age dynamics of estuarine particulate organicmatter using fatty acid δ13C and �14C composition. Limnol. Oceanogr. 60:611–28


Ann

u. R

ev. M

ar. S

ci. 2

016.

8:40

9-43

4. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

Acc

ess

prov

ided

by

Old

Dom

inio

n U

nive

rsity

on

02/2

6/18

. For

per

sona

l use

onl

y.


Medeiros PM, Sikes EL, Thomas B, Freeman KH. 2012. Flow discharge influences on input and transportof particulate and sedimentary organic carbon along a small temperate river. Geochim. Cosmochim. Acta77:317–34

Meyers PA. 1997. Organic geochemical proxies of paleoceanographic, paleolimnologic and paleoclimaticprocesses. Org. Geochem. 27:213–50

Middelburg JJ. 2014. Stable isotopes dissect aquatic food webs from the top to the bottom. Biogeosciences11:2357–71

Middelburg JJ, Barranguet C, Boschker HTS, Herman PMJ, Moens T, Heip CHR. 2000. The fate of intertidalmicrophytobenthos carbon: an in situ 13C-labeling study. Limnol. Oceanogr. 45:1224–34

Middelburg JJ, Herman PMJ. 2007. Organic matter processing in tidal estuaries. Mar. Chem. 106:127–47Middelburg JJ, Soetaert K, Herman P, Boschker HTS, Heip C. 2004. Burial of nutrients in coastal sediments:

the role of primary producers. See Nielsen et al. 2004, pp. 217–30Minor EC, Swenson MM, Mattson BM, Oyler AR. 2014. Structural characterization of dissolved organic

matter: a review of current techniques for isolation and analysis. Environ. Sci. Process. Impacts 16:2064–79Mitra S, Bianchi TS, Guo L, Santschi P. 2000. Terrestrially derived dissolved organic matter in the Chesapeake

Bay and the Middle Atlantic Bight. Geochim. Cosmochim. Acta 64:3547–57Moerdijk-Poortvliet TCW, Stal LJ, Boschker HTS. 2014. LC/IRMS analysis: a powerful technique to trace

carbon flow in microphytobenthic communities in intertidal sediments. J. Sea Res. 92:19–25Moran MA, Hodson RE. 1989. Formation and bacterial utilization of dissolved organic carbon derived from

detrital lignocellulose. Limnol. Oceanogr. 34:1034–47Neumann B, Vafeidis AT, Zimmermann J, Nicholls RJ. 2015. Future coastal population growth and exposure

to sea-level rise and coastal flooding—a global assessment. PLOS ONE 10:e0118571Nielsen SL, Banta GT, Pedersen MF, eds. 2004. Estuarine Nutrient Cycling: The Influence of Primary Producers.

Dordrecht, Neth.: Kluwer Acad.Oakes JM, Eyre BD, Middelburg JJ, Boschker HTS. 2010. Composition, production, and loss of carbohydrates

in subtropical shallow subtidal sandy sediments: rapid processing and long-term retention revealed by13C-labeling. Limnol. Oceanogr. 55:2126–38

Odum EP. 1968. A research challenge: evaluating the productivity of coastal and estuarine water. Presented at SeaGrant Conf., 2nd, Grad. Sch. Oceanogr., Univ. R.I., Narragansett

Opsahl S, Benner R. 1997. Distribution and cycling of terrigenous dissolved organic matter in the ocean.Nature 386:480–82

Osburn CL, Stedmon CA. 2011. Linking the chemical and optical properties of dissolved organic matter inthe Baltic-North Sea transition zone to differentiate three allochthonous inputs. Mar. Chem. 126:281–94

Pel R, Hoogveld H, Floris V. 2003. Using the hidden isotopic heterogeneity in phyto- and zooplankton tounmask disparity in trophic carbon transfer. Limnol. Oceanogr. 48:2200–7

Pomeroy LR, Wiegert RG. 1981. The Ecology of a Salt Marsh. New York: Springer-VerlagQian Y, Kennicutt MC, Svalberg J, Macko SA, Bidigare RR, Walker J. 1996. Suspended particulate organic

matter (SPOM) in Gulf of Mexico estuaries: compound-specific isotope analysis and plant pigment com-positions. Org. Geochem. 24:875–88

Raymond PA, Bauer JE. 2001. Use of 14C and 13C natural abundances for evaluating riverine, estuarine, andcoastal DOC and POC sources and cycling: a review and synthesis. Org. Geochem. 32:469–85

Richey JE, Melack JM, Aufdenkampe AK, Ballester VM, Hess LL. 2002. Outgassing from Amazonian riversand wetlands as a large tropical source of atmospheric CO2. Nature 416:617–20

Rodellas R, Garcia-Orellana J, Masque P, Feldman M, Weinstein Y. 2015. Submarine groundwater dischargeas a major source of nutrients to the Mediterranean Sea. PNAS 112:3926–30

Roman C, Jaworski N, Short F, Findlay S, Warren RS. 2000. Estuaries of the northeastern United States:habitat and land use signatures. Estuaries 23:743–64

Sachs JP, Schwab VF. 2011. Hydrogen isotopes in dinosterol from the Chesapeake Bay estuary. Geochim.Cosmochim. Acta 75:444–59

Saliot A, Tronczynski J, Scribe P, Letolle R. 1988. The application of isotopic and biogeochemical markers tothe study of the biochemistry of organic matter in a macrotidal estuary, the Loire, France. Estuar. Coast.Shelf Sci. 27:645–69


Ann

u. R

ev. M

ar. S

ci. 2

016.

8:40

9-43

4. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

Acc

ess

prov

ided

by

Old

Dom

inio

n U

nive

rsity

on

02/2

6/18

. For

per

sona

l use

onl

y.


Schouten S, Hopmans EC, Damste JSS. 2013. The organic geochemistry of glycerol dialkyl glycerol tetraetherlipids: a review. Org. Geochem. 54:19–61

Sicre MA, Tian RC, Saliot A. 1994. Distribution of sterols in the suspended particles of the Chang JiangEstuary and adjacent East China Sea. Org. Geochem. 21:1–10

Sikes EL, Uhle ME, Nodder SD, Howard ME. 2009. Sources of organic matter in a coastal marine envi-ronment: evidence from n-alkanes and their δ13C distributions in the Hauraki Gulf, New Zealand. Mar.Chem. 113:149–63

Slater GF, White HK, Eglinton TI, Reddy CM. 2005. Determination of microbial carbon sources in petroleumcontaminated sediments using molecular 14C analysis. Environ. Sci. Technol. 39:2552–58

Sleighter RL, Hatcher PG. 2008. Molecular characterization of dissolved organic matter (DOM) along a riverto ocean transect of the lower Chesapeake Bay by ultrahigh resolution electrospray ionization Fouriertransform ion cyclotron resonance mass spectrometry. Mar. Chem. 110:140–52

Smith EM, Benner R. 2005. Photochemical transformations of riverine dissolved organic matter: effects onestuarine bacterial metabolism and nutrient demand. Aquat. Microb. Ecol. 40:37–50

Spencer RGM, Ahad JME, Baker A, Cowie GL, Ganeshram R, et al. 2007. The estuarine mixing behaviour ofpeatland derived dissolved organic carbon and its relationship to chromophoric dissolved organic matterin two North Sea estuaries (UK). Estuar. Coast. Shelf Sci. 74:131–44

Stedmon CA, Markager S. 2005. Resolving the variability in dissolved organic matter fluorescence in a tem-perate estuary and its catchment using PARAFAC analysis. Limnol. Oceanogr. 50:686–97

Stubbins A, Lapierre JF, Berggren M, Prairie YT, Dittmar T, del Giorgio PA. 2014. What’s in an EEM?Molecular signatures associated with dissolved organic fluorescence in boreal Canada. Environ. Sci. Tech-nol. 48:10598–606

Tzortziou M, Neale P, Megonigal J, Pow C, Butterworth M. 2011. Spatial gradients in dissolved carbon dueto tidal marsh outwelling into a Chesapeake Bay estuary. Mar. Ecol. Prog. Ser. 426:41–56

Underwood GJC, Kromkamp J. 1999. Primary production by phytoplankton and microphytobenthos inestuaries. Adv. Ecol. Res. 29:93–153

van den Meersche K, Soetaert K, Middelburg JJ. 2011. Plankton dynamics in an estuarine plume: a mesocosm13C and 15N tracer study. Mar. Ecol. Prog. Ser. 429:29–43

van den Meersche K, Van Rijswijk P, Soetaert K, Middelburg JJ. 2009. Autochthonous and allochthonouscontributions to mesozooplankton diet in a tidal river and estuary: integrating carbon isotope and fattyacid constraints. Limnol. Oceanogr. 54:62–74

van Oevelen D, Moodley L, Soetaert K, Middelburg JJ. 2006. The trophic significance of bacterial carbon in amarine intertidal sediment: results of an in situ stable isotope labeling study. Limnol. Oceanogr. 51:2349–59

van Roosmalen L, Christensen JH, Butts MB, Jensen KH, Refsgaard JC. 2010. An intercomparison of regionalclimate model data for hydrological impact studies in Denmark. J. Hydrol. 380:406–19

Versteegh GJM, Schefub E, Dupont L, Marret F, Sinninghe JS, Jansen JHF. 2004. Taraxerol and Rhizophorapollen as proxies for tracking past mangrove ecosystems. Geochim. Cosmochim. Acta 68:411–22

Veuger B, Eyre BD, Maher D, Middelburg JJ. 2007. Nitrogen incorporation and retention by bacteria, algae,and fauna in a subtropical intertidal sediment: an in situ 15N-labeling study. Limnol. Oceanogr. 52:1930–42

Veuger B, Middelburg JJ, Boschker HTS, Houtekamer M. 2005. Analysis of 15N incorporation into D-alanine:a new method for tracing nitrogen uptake by bacteria. Limnol. Oceanogr. Methods 3:230–40

Volkman JK. 1986. A review of sterol markers for marine and terrigenous organic matter. Org. Geochem.9:83–99

Wakeham SG, McNichol AP, Kostka JE, Pease TK. 2006. Natural-abundance radiocarbon as a tracer ofassimilation of petroleum carbon by bacteria in salt marsh sediments. Geochim. Cosmochim. Acta 70:1761–71

Walsh EM, Ingalls AE, Keil RG. 2008. Sources and transport of terrestrial organic matter in Vancouver Islandfjords and the Vancouver-Washington Margin: a multiproxy approach using δ13Corg, lignin phenols, andthe ether lipid BIT index. Limnol. Oceanogr. 53:1054–63

Wang X-C, Callahan J, Chen RF. 2006. Variability in radiocarbon ages of biochemical compound classes ofhigh molecular weight dissolved organic matter in estuaries. Estuar. Coast. Shelf Sci. 68:188–94

Webster IT, Ford PW, Hodgson B. 2002. Microphytobenthos contribution to nutrient-phytoplankton dy-namics in a shallow coastal lagoon. Estuaries 25:540–51


Ann

u. R

ev. M

ar. S

ci. 2

016.

8:40

9-43

4. D

ownl

oade

d fr

om w

ww

.ann

ualr

evie

ws.

org

Acc

ess

prov

ided

by

Old

Dom

inio

n U

nive

rsity

on

02/2

6/18

. For

per

sona

l use

onl

y.


Weijers JWH, Schouten S, Schefuss E, Schneider RR, Damste JSS. 2009. Disentangling marine, soil and plantorganic carbon contributions to continental margin sediments: a multi-proxy approach in a 20,000 yearsediment record from the Congo deep-sea fan. Geochim. Cosmochim. Acta 73:119–32

Whitehead K. 2008. Marine organic geochemistry. In Chemical Oceanography and the Marine Carbon Cycle, ed.SR Emerson, JI Hedges, pp. 262–302. Cambridge, UK: Cambridge Univ. Press

Wozniak AS, Bauer JE, Sleighter RL, Dickhut RM, Hatcher PG. 2008. Technical Note: Molecular character-ization of aerosol-derived water soluble organic carbon using ultrahigh resolution electrospray ionizationFourier transform ion cyclotron resonance mass spectrometry. Atmos. Chem. Phys. 8:5099–111

Xu YP, Holmes CW, Jaffe R. 2007. Paleoenvironmental assessment of recent environmental changes in FloridaBay, USA: a biomarker based study. Estuar. Coast. Shelf Sci. 73:201–10

Ziervogel K, Arnosti C. 2009. Enzyme activities in the Delaware Estuary affected by elevated suspendedsediment load. Estuar. Coast. Shelf Sci. 84:253–58

Zimmerman AR, Canuel EA. 2000. A geochemical record of eutrophication and anoxia in Chesapeake Baysediments: anthropogenic influence on organic matter composition. Mar. Chem. 69:117–37

Zimmerman AR, Canuel EA. 2001. Bulk organic matter and lipid biomarker composition of Chesapeake Baysurficial sediments as indicators of environmental processes. Estuar. Coast. Shelf Sci. 53:319–41

Zimmerman AR, Canuel EA. 2002. Sediment geochemical records of eutrophication in the mesohaline Chesa-peake Bay. Limnol. Oceanogr. 47:1084–93


Ann

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l use

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MA08-FrontMatter ARI 9 December 2015 16:59

Annual Review ofMarine Science

Volume 8, 2016 Contents

Global Ocean Integrals and Means, with Trend ImplicationsCarl Wunsch � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 1

Visualizing and Quantifying Oceanic MotionT. Rossby � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �35

Cross-Shelf ExchangeK.H. Brink � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �59

Effects of Southern Hemisphere Wind Changes on the MeridionalOverturning Circulation in Ocean ModelsPeter R. Gent � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �79

Near-Inertial Internal Gravity Waves in the OceanMatthew H. Alford, Jennifer A. MacKinnon, Harper L. Simmons,

and Jonathan D. Nash � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � �95

Mechanisms of Physical-Biological-Biogeochemical Interaction at theOceanic MesoscaleDennis J. McGillicuddy Jr. � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 125

The Impact of Submesoscale Physics on Primary Productivityof PlanktonAmala Mahadevan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 161

Changes in Ocean Heat, Carbon Content, and Ventilation: A Reviewof the First Decade of GO-SHIP Global Repeat HydrographyL.D. Talley, R.A. Feely, B.M. Sloyan, R. Wanninkhof, M.O. Baringer,

J.L. Bullister, C.A. Carlson, S.C. Doney, R.A. Fine, E. Firing, N. Gruber,D.A. Hansell, M. Ishii, G.C. Johnson, K. Katsumata, R.M. Key, M. Kramp,C. Langdon, A.M. Macdonald, J.T. Mathis, E.L. McDonagh, S. Mecking,F.J. Millero, C.W. Mordy, T. Nakano, C.L. Sabine, W.M. Smethie,J.H. Swift, T. Tanhua, A.M. Thurnherr, M.J. Warner, and J.-Z. Zhang � � � � � � � � � 185

Characteristic Sizes of Life in the Oceans, from Bacteria to WhalesK.H. Andersen, T. Berge, R.J. Goncalves, M. Hartvig, J. Heuschele, S. Hylander,

N.S. Jacobsen, C. Lindemann, E.A. Martens, A.B. Neuheimer, K. Olsson,A. Palacz, A.E.F. Prowe, J. Sainmont, S.J. Traving, A.W. Visser, N. Wadhwa,and T. Kiørboe � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 217

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Mangrove Sedimentation and Response to Relative Sea-Level RiseC.D. Woodroffe, K. Rogers, K.L. McKee, C.E. Lovelock, I.A. Mendelssohn,

and N. Saintilan � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 243

The Great Diadema antillarum Die-Off: 30 Years LaterH.A. Lessios � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 267

Growth Rates of Microbes in the OceansDavid L. Kirchman � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 285

Slow Microbial Life in the SeabedBo Barker Jørgensen and Ian P.G. Marshall � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 311

The Thermodynamics of Marine Biogeochemical Cycles:Lotka RevisitedJoseph J. Vallino and Christopher K. Algar � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 333

Multiple Stressors in a Changing World: The Need for an ImprovedPerspective on Physiological Responses to the Dynamic MarineEnvironmentAlex R. Gunderson, Eric J. Armstrong, and Jonathon H. Stillman � � � � � � � � � � � � � � � � � � � � � � 357

Nitrogen and Oxygen Isotopic Studies of the Marine Nitrogen CycleKaren L. Casciotti � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 379

Sources, Ages, and Alteration of Organic Matter in EstuariesElizabeth A. Canuel and Amber K. Hardison � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 409

New Approaches to Marine Conservation Through the Scaling Up ofEcological DataGraham J. Edgar, Amanda E. Bates, Tomas J. Bird, Alun H. Jones,

Stuart Kininmonth, Rick D. Stuart-Smith, and Thomas J. Webb � � � � � � � � � � � � � � � � � � � � 435

Ecological Insights from Pelagic Habitats Acquired Using ActiveAcoustic TechniquesKelly J. Benoit-Bird and Gareth L. Lawson � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 463

Ocean Data Assimilation in Support of Climate Applications:Status and PerspectivesD. Stammer, M. Balmaseda, P. Heimbach, A. Kohl, and A. Weaver � � � � � � � � � � � � � � � � � � � 491

Ocean Research Enabled by Underwater GlidersDaniel L. Rudnick � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � � 519

Errata

An online log of corrections to Annual Review of Marine Science articles may be found athttp://www.annualreviews.org/errata/marine

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