PERSPECTIVE article

Front. Mar. Sci., 04 May 2017

Sec. Marine Ecosystem Ecology

Volume 4 - 2017 | https://doi.org/10.3389/fmars.2017.00125

Muddy Waters: Unintentional Consequences of Blue Carbon Research Obscure Our Understanding of Organic Carbon Dynamics in Seagrass Ecosystems

  • 1. Department of Biology and Chemistry, University of Bremen Bremen, Germany

  • 2. Centro de Estudios Avanzados de Blanes, Consejo Superior de Investigaciones Cientificas Blanes, Spain

  • 3. Center for Marine Ecosystems Research, Edith Cowan University Perth, WA, Australia

  • 4. Leibniz Centre for Tropical Marine Research Bremen, Germany

Abstract

The recent surge in research on organic carbon sequestration by seagrass ecosystems has begun to reveal the complexity of the carbon cycle within these ecosystems. In this prospective we discuss two areas of investigation that require further scrutiny: (1) why organic carbon is stabilized in seagrass sediments, and (2) how long organic carbon resides within these sediments. By delving into these topics, pointing out current pitfalls, and highlighting methodological advances, our motive is to focus future efforts and provide a frame work to manage the complexity found within the diverse seagrass bioregions. The high rate of seagrass degradation and loss, coupled with increasing atmospheric CO2 concentrations gives precedence to these lines of research, which require rigorous reevaluation if we are to substantially advance our understanding of OC dynamics in seagrass ecosystems.

Introduction

Seagrasses provide key ecological functions and services to coastal ecosystems, including sediment stabilization, coastline protection, nutrient cycling, support of fisheries, and enhancement of biodiversity (de la Torre-Castro and Rönnbäck, 2004; Duffy, 2006; Orth et al., 2006) due to the role they play as ecosystem engineers trapping sediment, altering hydrodynamics, and modifying biogeochemical processes in the water column and sediment (Marbá et al., 2006). From when seagrass meadows were recognized as potentially important “blue” carbon (organic carbon sequestered by vegetated coastal ecosystems) sinks, there has been a surge in efforts to determine the magnitude and variability of organic carbon (OC) storage within their sediments (Nellemann et al., 2009; Duarte et al., 2010, 2013; Fourqurean et al., 2012; Lavery et al., 2013; Campbell et al., 2014; Macreadie et al., 2014; Serrano et al., 2014, 2015, 2016b; Miyajima et al., 2015; Phang et al., 2015; Armitage and Fourqurean, ; Dahl et al., 2016; Jankowska et al., 2016; Röhr et al., 2016; Samper-Villarreal et al., 2016; Schile et al., 2016). Here, we point out two notable knowledge gaps, along with current methodological pitfalls, that are obscuring our ability to understand seagrass OC dynamics. First, we explore why OC is stabilized in coastal marine sediments, with emphasis on the need to look beyond a unifying mechanism governing OC storage across all seagrass ecosystems. Second, we address the question of how long OC is stored in seagrass sediments, with focus on how current methodologies may give misleading estimates of OC accumulation rates and residence times. Both of these topics have a rich a history of exploration and by pointing out common stumbling blocks our quest is to clarify the obstacles we face and propose a frame work for a direction forward. We hope to open dialogue and refocus efforts, so we do not repeat the past two decades of research, but instead utilize and build upon it to understand the unique dynamics of OC cycling in coastal marine sediments. Accelerating seagrass degradation and loss (Waycott et al., 2009) and rising atmospheric CO2 concentrations (IPCC, 2013) emphasize the relevance and timeliness of this discussion.

Why is OC stabilized in seagrass sediments?

Although it is important to identify where high carbon storage occurs in coastal marine landscapes, it is equally important to correctly identify why. In the past 5 years there has been a concerted effort to determine which environmental or biological variables predict carbon stock location and size across the broad range of seagrass bioregions (Lavery et al.,

2013

; Serrano et al.,

2014

,

2015

,

2016a

; Miyajima et al.,

2015

; Dahl et al.,

2016

; Röhr et al.,

2016

; Samper-Villarreal et al.,

2016

). An unintended consequence of searching for these broad unifying predictors is the potential to narrow our understanding of OC dynamics, which creates the risk of misidentifying why OC is stabilized within seagrass sediments. Within the process of OC stabilization, there is often a mechanism (crucial step or physiochemical condition) that disproportionally affects the stabilization or destabilization of organic matter (Torn et al.,

2009

). In the past two decades a paradigm shift in carbon research has broadened focus to include four primary mechanisms of OC stabilization (Sollins et al.,

1996

; Six et al.,

2004

; Burdige,

; Marschner et al.,

2008

; Torn et al.,

2009

; Trumbore,

2009

; Schmidt et al.,

2011

):

  • Inherent molecular characteristics of organic matter (recalcitrance).

  • Physical stabilization of OC on mineral surfaces.

  • Inaccessibility of OC to microbes due to barriers of interaction among microbes and substrates, such as occlusion of OC within aggregates.

  • Biotic suppression of microbial abundance and/or activity due to factors such as freezing temperatures, extreme pH, or low O2 content.

However, there is still a tendency within seagrass OC research to focus on correlative attributes of the seagrass, landscape, or sediment without direct investigation into the mechanism(s) of stabilization. Many propose carbon source mechanisms (recalcitrance) when explaining OC stabilization based largely on correlative isotopic (13C) evidence and seagrass tissue stoichiometry (C:N ratios, (Kennedy et al., 2010; Duarte et al., 2013; Serrano et al., 2015; Röhr et al., 2016). To definitively determine when, where, and to what extent recalcitrance controls OC stability in seagrass sediments there needs to be further research into the molecular composition of the OC (Vichkovitten and Holmer, 2005; Kaal et al., 2016), in tandem with rigorous investigation into its decomposability under the physical conditions experienced within the sediment. Several studies have shown sediment characteristics, such as grain size and type, to be important predictors for seagrass OC stocks (Dahl et al., 2016; Röhr et al., 2016; Serrano et al., 2016a), implying that biotic suppression (due to low O2 content within fine grain sediment) or physical stabilization on certain sediment types are potentially important mechanisms. The next steps must be taken to investigate molecular composition and decomposability, along with sediment mineralogy and geochemistry, and microbial diversity and activity (Mikutta et al., 2006; Chabbi et al., 2009; Schmidt et al., 2011; Simpson and Simpson, 2012; Macreadie et al., 2015; Bracho et al., ), if we are to draw definitive conclusions about why OC is stabilized in seagrass sediments.

Here, we outline some of the existing methodologies that can aid in our understanding of OC stabilization (Table 1). We have grouped methods under four broad lines of investigation: (1) determining the molecular composition of OC; (2) mapping the physical and chemical structure of the sediment environment; (3) tracing pathways and timelines of OC; and (4) revealing the identity, function, and activities of the sediment community. To substantially advance our understanding of OC dynamics in coastal marine ecosystems it will require a collaborative effort across disciplines, utilizing this broad spectrum of methodologies. However, this does not negate the importance of the continued efforts and expert knowledge of seagrass ecologists, who provide valuable insights and data required to understand the complex spatial and temporal variation of OC stabilization across seagrass ecosystems.

Table 1

UseMethodologyCitations
Investigating the molecular structure of organic matter in soils and sediments.Pyrolysis-Gas Chromatography/Mass Spectrometry (Py-GC/MS)Grandy and Neff, 2008; de la Rosa Arranz et al., 2009; Tolu et al., 2015
Nuclear magnetic resonance spectroscopy (NMR)Hedges et al., 2000; Kogel-Knabner, 2002, 2003; Chabbi et al., 2009; Simpson and Simpson, 2012
Near-edge X-ray Absorption Fine Structure (NEXAFS) spectroscopySolomon et al., 2004; Lehmann et al., 2005
Near-Infrared Spectroscopy (NIRS) / Fourier-Transform Infrared Spectroscopy (FTIR)Moros et al., 2008, 2010; Verchot et al., 2011; Fuentes et al., 2012; Vinduskova et al., 2015
Measuring and mapping of the physical and chemical structure of soils and sediments.X-ray fluorescence spectrometry / X-ray computed tomographyFeeney et al., 2006; Nunan et al., 2006; van Oort et al., 2006; West et al., 2007; Sleutel et al., 2008; Boyer-Villemaire et al.,
Scanning Transmission X-ray or Electron Microscopy (STXM & STEM)Brodowski et al., ; Maurice and Hochella, 2008; Remusat et al., 2012
Nano-scale secondary ion mass spectrometry (NanoSIMS)Herrmann et al., 2007; Amstalden van Hove et al., ; Remusat et al., 2012
MicrosensorsWerner et al., 2006; Dadi et al., 2015; Burdorf et al.,
Reconstructing sources, pathways and timescales organic matter in soils, including tracing microbial utilization.Compound-specific isotopic analysisRethemeyer et al., 2004; Ingalls et al., 2010; McIntosh et al., 2015
Biomarkers w/ stable- and natural-abundance radio-isotopesRethemeyer et al., 2004; Bouillon and Boschker, ; Amelung et al., ; Kramer et al., 2010; McIntosh et al., 2015
Low-level 14C pulse-chase labelingCarbone et al., 2007; Schuur et al., 2016
Stable isotope probing (SIP)Webster et al., 2006; Neufeld et al., 2007; Ruamps et al., 2011
Assessing biodiversity and functional diversity, and elucidating potential activities and interactions among sediment communities and their environment.Metagenomicsvon Mering et al., 2007; Maron et al., 2011; Paula et al., 2014; Bracho et al., ; Nesme et al., 2016; Pajares et al., 2016
MetatranscriptomicsCarvalhais et al., 2012; Jones et al., 2015; Thureborn et al., 2017
MetabolomicsBundy et al., ; Wallenstein and Weintraub, 2008; Kivlin and Hawkes, 2016

Some of the existing methodologies utilized to aid in the understanding of organic carbon stabilization in soils and sediments.

Not all methods fit cleanly into a specific category of usage and most can be used to investigate a variety of research questions.

How long is OC stabilized in seagrass sediments?

The second major knowledge gap we face is in our understanding of the timelines of OC stabilization within coastal marine sediments. This information, in addition to pool size, is critical for understanding the influence of seagrass carbon reservoirs on atmospheric CO2 concentrations. The ability of a reservoir to act as a net sink depends on both the fluxes of carbon into the reservoir and the timescale it is stabilized within it (Trumbore, 2000). Only systems with long carbon residence times (decades or longer) act as important mitigators for climate change.

The need to quantify timelines of carbon storage within seagrass sediments was pointed out two decade ago (Mateo et al., 1997, 2006); however, carbon accumulation rates and residence times have been reported based on estimates from age-depth relationships acquired by dating material within sediment layers (Mateo et al., 1997, 2010; Serrano et al., 2012, 2014, 2015, 2016b,c; Miyajima et al., 2015; Jankowska et al., 2016; Rozaimi et al., 2016) or by simply assuming sedimentation rates equal OC accumulation rates (Duarte et al., 2004; Kennedy et al., 2010; McLeod et al., 2011; Lavery et al., 2013; Macreadie et al., 2014; Röhr et al., 2016). These methodologies lead to an overestimation of OC ages and accumulation rates because they do not take into account decomposition losses (however small) from deeper sediment layers (Clymo, 1984; Korhola et al., 1995; Mateo et al., 1997). Furthermore, they ignore the addition of younger carbon (via root turnover and exudates) deeper in the sediment profile (Duarte et al., 1998, 2005). Even though many marine sediments vertically accrete, we must consider that OC does not accumulate in a static fashion, after deposition it continues to be cycled by microbes where it can be transformed and/or lost from the reservoir at rates that depend on the efficacy of the stabilization mechanisms (Torn et al., 2009). Additionally, seagrasses are vascular plants that transfer OC throughout the plant and exudate an estimated 6–17% of production via roots (Moriarty et al., 1986), which equates to various ages of carbon continuously entering the sediment pool.

Models can improve estimates of OC accumulation rates and residence times but have limitations. In an effort to account for OC decomposition, Clymo (1984) adapted a simple one-pool “box” model fit to cumulative carbon vs. age to achieve a more reasonable accumulation estimate that decreases as the stock grows. In this model decomposition is represented as a first-order process: dC/dt = − kCt, where C is the amount of carbon at a given time and k is the decomposition rate, and the residence time (also known as transit time) of the carbon within the pool is 1/k. To better represent sediment OC dynamics, which have continual OC inputs, this model was adapted as a multi-input system (vs. the decay of a single input; Trumbore and Harden, 1997; Manzoni et al., 2009, 2012; Hicks Pries et al., 2012), where both the decay constant and inputs can be estimated. Although these types of models have a rich history of usage for modeling OC dynamics, they are typically fit to data of mass loss through time (i.e., litter decomposition) or fluxes of CO2 (incubations; Eriksson, 1971; Bosatta and Agren, ; Ågren and Bosatta, ; Manzoni et al., 2009, 2012; Cornwell and Weedon, 2014). To fit them to data of cumulative OC vs. time (dated depths) from a sediment core the following assumptions must be made: (a) the system is in steady state; (b) initial OC in the sediment is zero; (c) carbon is accreted vertically (no inputs of new OC below dated depths); (d) the dated material is equal to the age of the bulk OC at the same depth in the sediment profile (see below); (e) there are no changes in OC dynamics through time, so recent OC dynamics (top of core) are representative of initial OC dynamics of the system. According to the above critique, none of these assumption holds true for the actual situation and OC dynamics in marine sediments. On top of this, it is assumed the entire core is one pool of OC, all residing for the same time period, and although multi-pool box models exist, the data from sediment cores often do not support the increased model complexity. Furthermore, the use of cumulative data, which are not independent, leads to unrealistic confidence in model estimates (due to underestimation of model uncertainty; King et al., 2015). In spite of these limitations, these models have proven to be useful for providing more realistic estimates of OC accumulation and residence time of OC within non-vascular dominated, vertically-accreting ecosystems (Clymo, 1984; Trumbore and Harden, 1997; Hicks Pries et al., 2012). However, extreme caution must be used when applying them to sediment-core data from vascular plant dominated ecosystems such as seagrass meadows.

Another factor that influences estimates of OC ages and residence times is the type of material used for dating. Previous works in seagrass ecosystems have utilized closed-system materials (assumed to be no longer exchanging carbon with the environment), such as shells or sheaths, for radiocarbon (14C) dating (Mateo et al., 1997, 2010; Serrano et al., 2012, 2014, 2015, 2016b,c; Rozaimi et al., 2016). Because sediment OC consist of a spectrum of pools cycling on different time scales, choosing the oldest, most stable carbon within the sediment and ignoring all other OC (of a variety of ages) residing at the same depth in the sediment profile, leads to an overestimation of OC ages and residence times (Trumbore and Zheng, 1996; Torn et al., 2009; Trumbore, 2009; Trumbore et al., 2016). To illustrate the potential for overestimation, OC ages have been shown to vary by three orders of magnitude, from 3 years (Δ14C = +170‰) to ~3,000 (Δ14C = −310‰) years, within a 5-cm sediment layer in tropical forest soils (Trumbore and Zheng, 1996; Trumbore, 2009). Therefore, when the goal is to understand OC dynamics, and estimates of residence times of the various carbon pools are needed (as opposed to exact calendar ages), a different methodological approach is required.

Because of the limitations outlined above we suggest an alternative methodology utilized in terrestrial systems over the past two decades (Trumbore, 1993, 2000, 2009; Schuur et al., 2016). Organic matter is more appropriately thought of as a heterogeneous open-system (continuously exchanging carbon with its environment), so directly measuring 14C of the bulk sediment OC pool along with manually separating and dating pools (that are relatively homogenous in terms of decomposition rates) provide more realistic estimates of the suite OC ages occurring within the sediment (Trumbore, 2009; Schuur et al., 2016; Trumbore et al., 2016). Since OC is a complex mixture of compounds that cycle along a continuum of time scales from minutes to millennia, no separation method will be perfect. However, methods exist to partition OC into various pools, which allows for the determination of both pool size and residence time (Trumbore and Zheng, 1996; von Lützow et al., 2007; Trumbore, 2009; Trumbore et al., 2016). The same linear-system box models can be adapted to estimate the residence time of 14C of each pool: where λ is the radioactive decay constant (1.21 × 10−4 yr−1), I*14C(t) are the inputs of 14C based off a time series of 14C from of the reservoir the plant uptakes CO2 from, and k*14C(t) are the estimated outputs. These models can also be extended to multi-pool models and only requires a measurement from your desired pool of either the F (fraction modern prior to 1950) or F' (fraction modern that includes bomb 14C) and a bomb carbon time series of F' of the reservoir (Manzoni et al., 2009, 2012; Trumbore et al., 2016). For terrestrial systems, the time series of the reservoir (atmosphere) F' is well known (Hua et al., 2013), but becomes more complicated in marine systems because of the reservoir effect (Mangerud, 1972; Stuiver et al., 1986). However, in many coastal systems, post-bomb 14C time series exist (Weidman and Jones, 1993; Kalish et al., 2001; Mahadevan, 2001; Kilada et al., 2007; Scourse et al., 2012; Tisnérat-Laborde et al., 2013). Another potential hurdle in marine systems is the presence of terrestrial carbon (fixed from the atmospheric pool), so care must be taken to disentangle these signals (Marshall et al., 2007; Yu et al., 2007). Although there are some hurdles, this methodology avoids complications created by simplistic assumptions of carbon ages and depths, and provides direct measurements of residence times directly linked to pools of known sizes and locations. These techniques could be used in tandem with attributes of the OC pool and sediment (such as mineralogy, redox, and molecular composition), to advance our understanding of the timescales over which different stabilization mechanisms operate (Mikutta et al., 2006; Chabbi et al., 2009).

A way forward

Here, we propose a conceptual framework to focus research efforts across the diverse environments where seagrasses occur. This framework is adapted from the Jenny (1941) state-factor system utilized in terrestrial ecosystems, to incorporate factors identified for subaqueous soils (Demas and Rabenhorst, 2001; Torn et al., 2009; Trumbore, 2009). In this model a soil property such as OC storage is described by the function: where C = climate, O = organism (vegetation), B = bathymetry, F = flow regime, P = parent material, T = time). These factors set the boundary conditions and modulate the mechanisms that determine the magnitude and timescales of carbon stabilization (Figure 1). By selecting study sites where one state-factor varies, while the other factors are held relatively constant, we can begin to identify the role each factor plays and what mechanism(s) operate within the unique combination of state-factors that occur throughout the seagrass bioregions (Short et al., 2007). For example, within Posidonia spp. meadows OC storage varies predictably with bathymetry in sheltered bays (flow regime) in both the Mediterranean and Western Australia (Serrano et al., 2014), with the difference in magnitude of OC storage between the locations potentially explained by variations between seagrass species (organism-vegetation). The usefulness of this framework can be further illustrated by the finding that across the European geographic distribution (climate) of Zostera marina (organism-vegetation), OC can be predicted by sediment grain size (parent material and/or flow regime; (Dahl et al., 2016). Furthermore, in two sites with contrasting sediment characteristics they found that OC did not decrease with sediment depth (indicating minimal decomposition over time), which lead to the hypothesis that different stabilization mechanisms were at play: a) biotic suppression due to low oxygen availability in the fine-grain site, and b) recalcitrance of allochthonous carbon inputs in the course-grain site. This framework can also potentially explain why sediment grain size does not correlate to OC storage when looking across a mixture of different parent materials, climates, seagrass species, flow regimens, and bathymetry (Serrano et al., 2016a). We believe that embracing the complexity found within seagrass ecosystems and utilizing the state-factor system to systematically identify which mechanism(s) control the spatial and temporal variations of OC is a way forward to understand carbon dynamics in coastal marine systems.

Figure 1

Conclusion

As policy makers and managers identify pathways to conserve seagrass systems embedded under a blue carbon framework (Herr et al., 2012), the potential for OC sequestration opens the door for both positive and negative consequences. On the positive side, this creates an avenue for conservation of these valuable ecosystems, along with their well-established ecosystem services. On the negative side, CO2 will be emitted in exchange for carbon credits, resulting in an increase in atmospheric CO2 unless we are able to correctly estimate the magnitude and timelines of OC sequestration. The future of blue carbon research is not trivial. There are both spatial and temporal scales on which OC stabilization/destabilization mechanisms operate, with complex processes and controls working in combination. As we come to terms with this complexity, and embrace technological advances in genetic, molecular, spectrometric, and isotope-tracing techniques in tandem with gathering more data from a diversity of seagrass ecosystems, we can move forward with this important line of research.

Funding

The work leading to this publication was supported by the German Academic Exchange Service (DAAD) with funds from the German Federal Ministry of Education and Research (BMBF) and the People Programme (Marie Curie Actions) of the European Union's Seventh Framework Programme (FP7/2007-2013) under REA grant agreement n° 605728 (PRIME—Postdoctoral Researchers International Mobility Experience), and the projects SUMILEN (CTM2013-47728-R) and PALEOPARK (1104/2014), funded by the Spanish National Parks and State Research Schemes.

Conflict of interest statement

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

Statements

Author contributions

EB produced the conceptual framework, wrote the first draft of the manuscript, and synthesized the inputs and revisions of the coauthors. MM contributed to the conceptual knowledge and critically revised the manuscript. LG contributed to the conceptual knowledge and critically revised the manuscript. MZ contributed to the conceptual knowledge and critically revised the manuscript. MT contributed to the conceptual knowledge and critically revised the manuscript.

Acknowledgments

We would like to acknowledge Caitlin Hicks-Pries for conceptual help on alternative ways to subsample and radiocarbon date sediment cores, and Jose Sanjuan Munoz for helping us to understand and model using input-output box models.

Conflict of interest

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

References

  • 1

    ÅgrenG. I.BosattaE. (1996). A bridge between theory and experiment in soil organic matter studies. Oikos76, 522–528. 10.2307/3546345

  • 2

    AmelungW.BrodowskiS.Sandhage-HofmannA.BolR. (2008). Combining biomarker with stable isotope analyses for assessing the transformation and turnover of soil organic matter. Adv. Agron.100, 155–250. 10.1016/S0065-2113(08)00606-8

  • 3

    Amstalden van HoveE. R.SmithD. F.HeerenR. M. A. (2010). A concise review of mass spectrometry imaging. J. Chromatogr. A1217, 3946–3954. 10.1016/j.chroma.2010.01.033

  • 4

    ArmitageA. R.FourqureanJ. W. (2016). Carbon storage in seagrass soils: long-term nutrient history exceeds the effects of near-term nutrient enrichment. Biogeosciences13, 313–321. 10.5194/bg-13-313-2016

  • 5

    BosattaE.AgrenG. I. (1985). Theoretical analysis of decomposition of heterogeneous substrates. Soil Biol. Biochem.17, 601–610. 10.1016/0038-0717(85)90035-5

  • 6

    BouillonS.BoschkerH. T. S. (2006). Bacterial carbon sources in coastal sediments: a cross-system analysis based on stable isotope data of biomarkers. Biogeosciences3, 175–185. 10.5194/bg-3-175-2006

  • 7

    Boyer-VillemaireU.St-OngeG.BernatchezP.LajeunesseP.LabrieJ. (2013). High-resolution multiproxy records of sedimentological changes induced by dams in the Sept-Îles area (Gulf of St. Lawrence, Canada). Mar. Geol.338, 17–29. 10.1016/j.margeo.2012.11.012

  • 8

    BrachoR.NataliS.PegoraroE.CrummerK. G.SchadelC.CelisG.et al. (2016). Temperature sensitivity of organic matter decomposition of permafrost-region soils during laboratory incubations. Soil Biol. Biochem.97, 1–14. 10.1016/j.soilbio.2016.02.008

  • 9

    BrodowskiS.AmelungW.HaumaierL.AbetzC.ZechW. (2005). Morphological and chemical properties of black carbon in physical soil fractions as revealed by scanning electron microscopy and energy-dispersive X-ray spectroscopy. Geoderma128, 116–129. 10.1016/j.geoderma.2004.12.019

  • 10

    BundyJ. G.DaveyM. P.ViantM. R. (2008). Environmental metabolomics: a critical review and future perspectives. Metabolomics5, 3–21. 10.1007/s11306-008-0152-0

  • 11

    BurdigeD. J. (2007). Preservation of organic matter in marine sediments: controls, mechanisms, and an imbalance in sediment organic carbon budgets?Chem. Rev.107, 467–485. 10.1021/cr050347q

  • 12

    BurdorfL.Hidalgo-MartinezS.CookP.MeysmanF. (2016). Long-distance electron transport by cable bacteria in mangrove sediments. Mar. Ecol. Prog. Series545, 1–8. 10.3354/meps11635

  • 13

    CampbellJ. E.LaceyE. A.DeckerR. A.CrooksS.FourqureanJ. W. (2014). Carbon Storage in Seagrass Beds of Abu Dhabi, United Arab Emirates. Estuaries Coasts38, 243–251. 10.1007/s12237-014-9802-9

  • 14

    CarboneM. S.CzimczikC. I.McDuffeeK. E.TrumboreS. E. (2007). Allocation and residence time of photosynthetic products in a boreal forest using a low-level 14C pulse-chase labeling technique. Global Change Biol.13, 466–477. 10.1111/j.1365-2486.2006.01300.x

  • 15

    CarvalhaisL. C.DennisP. G.TysonG. W.SchenkP. M. (2012). Application of metatranscriptomics to soil environments. J. Microbiol. Methods91, 246–251. 10.1016/j.mimet.2012.08.011

  • 16

    ChabbiA.Kogel-KnabnerI.RumpelC. (2009). Stabilised carbon in subsoil horizons is located in spatially distinct parts of the soil profile. Soil Biol. Biochem.41, 256–261. 10.1016/j.soilbio.2008.10.033

  • 17

    ClymoR. S. (1984). The limits to Peat Bog growth. Philosophical Trans. R. Soc. London B Biol. Sci.303, 605–654. 10.1098/rstb.1984.0002

  • 18

    CornwellW. K.WeedonJ. T. (2014). Decomposition trajectories of diverse litter types: a model selection analysis. Methods Ecol. Evol.5, 173–182. 10.1111/2041-210X.12138

  • 19

    DadiT.VölknerC.KoschorreckM. (2015). A sediment core incubation method to measure the flux of dissolved organic carbon between sediment and water. J. Soils Sediments15, 2350–2358. 10.1007/s11368-015-1213-4

  • 20

    DahlM.DeyanovaD.GütschowS.AsplundM. E.LyimoL. D.KaramfilovV.et al. (2016). Sediment properties as important predictors of carbon storage in Zostera marina meadows: a comparison of four European areas. PLoS ONE11:e0167493. 10.1371/journal.pone.0167493

  • 21

    DemasG. P.RabenhorstM. C. (2001). Factors of subaqueous soil formation: a system of quantitative pedology for submersed environments. Geoderma102, 189–204. 10.1016/S0016-7061(00)00111-7

  • 22

    de la Rosa ArranzJ. M.González-VilaF. J.López-CapelE.ManningD. A. C.KnickerH.González-PérezJ. A. (2009). Structural properties of non-combustion-derived refractory organic matter which interfere with BC quantification. J. Anal. Appl. Pyrol.85, 399–407. 10.1016/j.jaap.2008.11.019

  • 23

    de la Torre-CastroM.RönnbäckP. (2004). Links between humans and seagrasses—an example from tropical East Africa. Ocean Coast. Manage.47, 361–387. 10.1016/j.ocecoaman.2004.07.005

  • 24

    DuarteC. M.HolmerM.MarbaN. (2005). Plant-Microbe Interactions in Seagrass Meadows in Macroand Microorganisms. Mar. Sediments Coast. Estuarine Stud.60, 1–30. 10.1029/ce060p0031

  • 25

    DuarteC. M.KennedyH.MarbaN.HendriksI. (2013). Assessing the capacity of seagrass meadows for carbon burial: current limitations and future strategies. Ocean Coast. Manage.83, 32–38. 10.1016/j.ocecoaman.2011.09.001

  • 26

    DuarteC. M.MarbaN.GaciaE.FourqureanJ. W.BegginsJ.BarronC.et al. (2010). Seagrass community metabolism: assessing the carbon sink capacity of seagrass meadows. Global Biogeochem. Cycles24:GB4032. 10.1029/2010GB003793

  • 27

    DuarteC. M.MerinoM.AgawinN. S. R.UriJ.FortesM. D.GallegosM. E.et al. (1998). Root production and belowground seagrass biomass. Mar. Ecol. Prog. Ser.171, 97–108. 10.3354/meps171097

  • 28

    DuarteC. M.MiddelburgJ. J.CaracoN. (2004). Major role of marine vegetation on the oceanic carbon cycle. Biogeosci. Discuss.1, 659–679. 10.5194/bgd-1-659-2004

  • 29

    DuffyJ. E. (2006). Biodiversity and the functioning of seagrass ecosystems. Mar. Ecol. Prog. Ser.311, 233–250. 10.3354/meps311233

  • 30

    ErikssonE. (1971). Compartment models and reservoir theory. Ann. Rev. Ecol. Syst.2, 67–84. 10.1146/annurev.es.02.110171.000435

  • 31

    FeeneyD. S.CrawfordJ. W.DaniellT.HallettP. D.NunanN.RitzK.et al. (2006). Three-dimensional microorganization of the soil–root–microbe system. Microb Ecol.52, 151–158. 10.1007/s00248-006-9062-8

  • 32

    FourqureanJ. W.DuarteC. M.KennedyH.MarbaN.HolmerM.MateoM. A.et al. (2012). Seagrass ecosystems as a globally significant carbon stock. Nat. Geosci.5, 505–509. 10.1038/ngeo1477

  • 33

    FuentesM.HidalgoC.González-MartínI.Hernández-HierroJ. M.GovaertsB.SayreK. D.et al. (2012). NIR Spectroscopy: an alternative for soil analysis. Commun. Soil Sci. Plant Anal.43, 346–356. 10.1080/00103624.2012.641471

  • 34

    GrandyA. S.NeffJ. C. (2008). Molecular C dynamics downstream: The biochemical decomposition sequence and its impact on soil organic matter structure and function. Sci. Total Environ.404, 297–307. 10.1016/j.scitotenv.2007.11.013

  • 35

    HedgesJ. I.EglintonG.HatcherP. G.KirchmanD. L.ArnostiC.DerenneS.et al. (2000). The molecularly-uncharacterized component of nonliving organic matter in natural environments. Org. Geochem.31, 945–958. 10.1016/s0146-6380(00)00096-6

  • 36

    HerrD.PidgeonE.LaffoleyD. eds. (2012). Blue Carbon Policy Framework: Based on the Discussion of the International Blue Carbon Policy Working Group Gland.Switzerland: IUCN and Arlington.

  • 37

    HerrmannA. M.RitzK.NunanN.ClodeP. L.Pett-RidgeJ.KilburnM. R.et al. (2007). Nano-scale secondary ion mass spectrometry — A new analytical tool in biogeochemistry and soil ecology: a review article. Soil Biol. Biochem.39, 1835–1850. 10.1016/j.soilbio.2007.03.011

  • 38

    Hicks PriesC. E.SchuurE.CrummerK. (2012). Holocene carbon stocks and carbon accumulation rates altered in soils undergoing permafrost thaw. Ecosystems15, 162–173. 10.1007/s10021-011-9500-4

  • 39

    HuaQ.BarbettM.RakowskiA. Z. (2013). Atmospheric radiocarbon for the period 1950-2010. Radiocarbon55, 2059–2072. 10.2458/azu_js_rc.v55i2.16177

  • 40

    IngallsA. E.EllisE. E.SantosG. M.McDuffeeK. E.TruxalL.KeilR. G.et al. (2010). HPLC purification of higher plant-dervied lignin phenols for compound specific radiocarbon analysis. Anal. Chem.82, 8931–8938. 10.1021/ac1016584

  • 41

    IPCC (2013). Summary for Policymakers in Climate Change The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, eds. StockerT. F.QinD.PlattnerG. K.TignorM.AllenS. K.BoschungJ. (Cambridge; New York, NY: Cambridge University Press), 1–28.

  • 42

    JankowskaE.MichelL. N.ZaborskaA.Włodarska KowalczukM. (2016). Sediment carbon sink in low-density temperate eelgrass meadows (Baltic Sea). J. Geophys. Res. Biogeo121, 2918–2934. 10.1002/2016jg003424

  • 43

    JennyH. (1941). Factors of Soil Formation. New York, NY: McGraw Hill.

  • 44

    JonesD. S.FloodB. E.BaileyJ. V. (2015). Metatranscriptomic insights into polyphosphate metabolism in marine sediments. ISME J.10, 1015–1019. 10.1038/ismej.2015.169

  • 45

    KaalJ.SerranoO.NieropK. G. J.SchellekensJ.Martínez CortizasA.MateoM. A. (2016). Molecular composition of plant parts and sediment organic matter in a Mediterranean seagrass (Posidonia oceanica) mat. Aquatic Bot.133, 50–61. 10.1016/j.aquabot.2016.05.009

  • 46

    KalishJ. M.NydalR.NedreaasK. H.BurrG. S.EineG. L. (2001). A time history of pre- and post-bomb radiocarbon in the barents sea derived from arcto-norwegian cod otoliths. Radiocarbon43, 843–855. 10.1017/S0033822200041515

  • 47

    KennedyH.BegginsJ.DuarteC. M.FourqureanJ. W.HolmerM.MarbaN.et al. (2010). Seagrass sediments as a global carbon sink: Isotopic constraints. Global Biogeochem. Cycles24:GB4026. 10.1029/2010GB003848

  • 48

    KiladaR. W.CampanaS. E.RoddickD. (2007). Validated age, growth, and mortality estimates of the ocean quahog (Arctica islandica) in the western Atlantic. ICES J. Mar. Sci.64, 31–38. 10.1093/icesjms/fsl001

  • 49

    KingA. A.Domenech de CellesM.MagpantayF.RohaniP. (2015). Avoidable errors in the modeling of outbreaks of emerging pathogens, with special reference to Ebola. Proc. R. Soc. B282, 20150347. 10.1098/rspb.2015.0347

  • 50

    KivlinS. N.HawkesC. V. (2016). Temporal and spatial variation of soil bacteria richness, composition, and function in a neotropical rainforest. PLoS ONE11:e0159131. 10.1371/journal.pone.0159131

  • 51

    Kogel-KnabnerI. (2002). The macromolecular organic composition of plant and microbial residues as inputs to soil organic matter. Soil Biol. Biochem.34, 139–162. 10.1002/chin.200223287

  • 52

    Kogel-KnabnerI. (2003). 13C and 15N NMR spectroscopy as a tool in soil organic matter studies. Gerderma80, 243–270. 10.1016/S0016-7061(97)00055-4

  • 53

    KorholaA.TolonenK.TurunenJ.JungnerH. (1995). Estimating long-term carbon accumulation rates in boreal peatlands by radiocarbon dating. Radiocarbon37, 575–584. 10.1017/S0033822200031064

  • 54

    KramerC.TrumboreS.FrObergM.DozalL. M. C.ZhangD.XuX.et al. (2010). Recent (<4 year old) leaf litter is not a major source of microbial carbon in a temperate forest mineral soil. Soil Biol. Biochem.42, 1028–1037. 10.1016/j.soilbio.2010.02.021

  • 55

    LaveryP. S.MateoM. A.SerranoO.RozaimiM. (2013). Variability in the carbon storage of seagrass habitats and its implications for global estimates of blue carbon ecosystem service. PLoS ONE8:e73748. 10.1371/journal.pone.0073748

  • 56

    LehmannJ.LiangB.SolomonD.LeroticM.LuizãoF.KinyangiJ.et al. (2005). Near-edge X-ray absorption fine structure (NEXAFS) spectroscopy for mapping nano-scale distribution of organic carbon forms in soil: Application to black carbon particles. Global Biogeochem. Cycles19:GB1013. 10.1029/2004GB002435

  • 57

    MacreadieP. I.BairdM. E.Trevathan-TackettS. M.LarkumA. W. D.RalphP. J. (2014). Quantifying and modelling the carbon sequestration capacity of seagrass meadows – A critical assessment. Mar. Pollut. Bull.83, 30–439. 10.1016/j.marpolbul.2013.07.038

  • 58

    MacreadieP. I.Trevathan-TackettS. M.SkilbeckC. G.SandermanJ.CurlevskiN.JacobsenG.et al. (2015). Losses and recovery of organic carbon from a seagrass ecosystem following disturbance. Proc. R. Soc. B282:20151537. 10.1098/rspb.2015.1537

  • 59

    MahadevanA. (2001). An analysis of bomb radiocarbon trends in the Pacific. Mar. Chem.73, 273–290. 10.1016/S0304-4203(00)00113-4

  • 60

    MangerudJ. (1972). Radiocarbon dating of marine shells, including a discussion of apparent age of recent shells from Norway. Boreas1, 143–172. 10.1111/j.1502-3885.1972.tb00147.x

  • 61

    ManzoniS.KatulG. G.PorporatoA. (2009). Analysis of soil carbon transit times and age distributions using network theories. J. Geophys. Res114:G04025. 10.1029/2009jg001070

  • 62

    ManzoniS.PiñeiroG.JacksonR. B.JobbágyE. G.KimJ. H.PorporatoA. (2012). Analytical models of soil and litter decomposition: solutions for mass loss and time-dependent decay rates. Soil Biol. Biochem.50, 66–76.

  • 63

    MarbáN.HolmerM.GaciaE.BarronC. (2006). Seagrass beds and coastal biogeochemistry, in Seagrasses: Biology, Ecology and Conservation, eds LarkumA. W. D.OrthR. J.DuarteC. M. (Dordrecht: Springer), 135–157.

  • 64

    MaronP.-A.MougelC.RanjardL. (2011). Soil microbial diversity: Methodological strategy, spatial overview and functional interest. C. R. Biol.334, 403–411. 10.1016/j.crvi.2010.12.003

  • 65

    MarschnerB.BrodowskiS.DrevesA.GleixnerG.GudeA.GrootesP. M.et al. (2008). How relevant is recalcitrance for the stabilization of organic matter in soils?J. Plant Nutr. Soil Sci.171, 91–110. 10.1002/jpln.200700049

  • 66

    MarshallW. A.GehrelsW. R.GarnettM. H.FreemanS. P. H. T.MadenC.XuS. (2007). The use of “bomb spike” calibration and high-precision AMS 14C analyses to date salt-marsh sediments deposited during the past three centuries. Quaternary Res.68, 325–337. 10.1016/j.yqres.2007.07.005

  • 67

    MateoM. A.CebrianJ.DuntonK. H.MutchlerT. (2006). Carbon Flux in Seagrass Ecosystems, in Seagrasses: Biology, Ecology and Conservation, eds LarkumA. W. D.OrthR. J.DuarteC. M. (Dordrecht: Springer), 159–192.

  • 68

    MateoM. Á.RenomP.MichenerR. H. (2010). Long-term stability in the production of a NW Mediterranean Posidonia oceanica (L.) Delile meadow. Palaeogeogr. Palaeoclimatol. Palaeoecol.291, 286–296. 10.1016/j.palaeo.2010.03.001

  • 69

    MateoM. A.RomeroJ.PerezaM.LittlerM. M.LittlerD. S. (1997). Dynamics of millenary organic deposits resulting from the growth of the mediterranean seagrass Posidonia oceanica. Estuarine Coast. Shelf Sci.44, 103–110. 10.1006/ecss.1996.0116

  • 70

    MauriceP. A.HochellaM. F. (2008). Nanoscale Particles and Processes: A New Dimension in Soil Science, 1st Edn.Cambridge, MA: Elsevier Inc.

  • 71

    McIntoshH. A.McNicholA. P.XuL.CanuelE. A. (2015). Source-age dynamics of estuarine particulate organic matter using fatty acid δ13C and Δ 14C composition. Limnol. Oceanogr.60, 611–628. 10.1002/lno.10053

  • 72

    McLeodE.ChmuraG. L.BouillonS.SalmR.BjörkM.DuarteC. M.et al. (2011). A blueprint for blue carbon: toward an improved understanding of the role of vegetated coastal habitats in sequestering CO2. Front. Ecol. Environ.9, 552–560. 10.1890/110004

  • 73

    MikuttaR.KleberM.TornM. S.JahnR. (2006). Stabilization of soil organic matter: association with minerals or chemical recalcitrance?Biogeochemistry77, 25–56. 10.1007/s10533-005-0712-6

  • 74

    MiyajimaT.HoriM.HamaguchiM.ShimabukuroH.AdachiH.YamanoH.et al. (2015). Geographic variability in organic carbon stock and accumulation rate in sediments of East and Southeast Asian seagrass meadows. Global Biogeochem. Cycles29, 1–19. 10.1002/2014GB004979

  • 75

    MoriartyD. J. W.IversonR. L.PollardP. C. (1986). Exudation of organic carbon by the seagrass Halodule wrightii Aschers. And its effect on bacterial growth in the sediment. J. Exp. Mar. Biol. Ecol.96, 115–126. 10.1016/0022-0981(86)90237-6

  • 76

    MorosJ.Barciela-AlonsoM. C.Pazos-CapeánsP.Bermejo-BarreraP.Peña-VázquezE.GarriguesS.et al. (2008). Characterization of estuarine sediments by near infrared diffuse reflectance spectroscopy. Anal. Chim. Acta624, 113–127. 10.1016/j.aca.2008.06.030

  • 77

    MorosJ.CassellaR. J.Barciela-AlonsoM. C.Moreda-PiñeirocA.Herbello-HermeloP.Bermejo-BarreraP.et al. (2010). Estuarine sediment quality assessment by Fourier-transform infrared spectroscopy. Vibrational Spectrosc.53, 204–213. 10.1016/j.vibspec.2010.03.001

  • 78

    NellemannC.CorcoranE.DuarteC. M.ValdesL.De YoungC.FonsecaL.et al. (eds). (2009). Blue Carbon. Norway Available online at: www.grida.no

  • 79

    NesmeJ.AchouakW.AgathosS. N.BaileyM.BaldrianP.BrunelD.et al. (2016). Back to the future of soil metagenomics. Front. Microbiol.7:73. 10.3389/fmicb.2016.00073

  • 80

    NeufeldJ. D.WagnerM.MurrellJ. C. (2007). Who eats what, where and when? Isotope-labelling experiments are coming of age. ISME J.1, 103–110. 10.1038/ismej.2007.30

  • 81

    NunanN.RitzK.RiversM.FeeneyD. S.YoungI. M. (2006). Investigating microbial micro-habitat structure using X-ray computed tomography. Geoderma133, 398–407. 10.1016/j.geoderma.2005.08.004

  • 82

    OrthR. J.CarruthersT. J. B.DennisonW. C.DuarteC. M.FourqureanJ. W.HeckK. L.et al. (2006). A global crisis for seagrass ecosystems. Bioscience56, 987–996. 10.1641/0006-3568(2006)56[987:AGCFSE]2.0.CO;2

  • 83

    PajaresS.EscalanteA. E.NoguezA. M.García-OlivaF.Martínez-PiedragilC.CramS. S.et al. (2016). Spatial heterogeneity of physicochemical properties explains differences in microbial composition in arid soils from Cuatro Cienegas, Mexico. PeerJ.4, e2459–e2420. 10.7717/peerj.2459

  • 84

    PaulaF. S.RodriguesJ. L. M.ZhouJ.WuL.MuellerR. C.MirzaB. S.et al. (2014). Land use change alters functional gene diversity, composition and abundance in Amazon forest soil microbial communities. Mol. Ecol.23, 2988–2999. 10.1111/mec.12786

  • 85

    PhangV.ChouL. M.FriessD. A. (2015). Ecosystem carbon stocks across a tropical intertidal habitat mosaic of mangrove forest, seagrass meadow, mudflat and sandbar. Earth Surf. Process. Landforms40, 1387–1400. 10.1002/esp.3745

  • 86

    RemusatL.HattonP.-J.NicoP. S.ZellerB.KleberM.DerrienD. (2012). NanoSIMS study of organic matter associated with soil aggregates: advantages, limitations, and combination with STXM. Environ. Sci. Technol.46, 3943–3949. 10.1021/es203745k

  • 87

    RethemeyerJ.KramerC.GleixnerG.WiesenbergG. L. B.SchwarkL.AndersenN.et al. (2004). Complexity of soil organic matter: AMS 14C analysis of soil lipid fractions and individual compounds. Radiocarbon46, 465–473. 10.1017/S0033822200039771

  • 88

    RöhrM. E.BoströmC.Canal-VergésP.HolmerM. (2016). Blue carbon stocks in Baltic Sea eelgrass (Zostera marina) meadows. Biogeosciences13, 6139–6153. 10.5194/bg-13-6139-2016

  • 89

    RozaimiM.LaveryP. S.SerranoO. (2016). Long-term carbon storage and its recent loss in an estuarine Posidonia australis meadow (Albany, Western Australia). Estuar. Coast. Shelf Sci.171, 58–65. 10.1016/j.ecss.2016.01.001

  • 90

    RuampsL. S.NunanN.ChenuC. (2011). Microbial biogeography at the soil pore scale. Soil Biol. Biochem.43, 280–286. 10.1016/j.soilbio.2010.10.010

  • 91

    Samper-VillarrealJ.LovelockC. E.SaundersM. I.RoelfsemaC.MumbyP. J. (2016). Organic carbon in seagrass sediments is influenced by seagrass canopy complexity, turbidity, wave height, and water depth. Limnol. Oceanogr.61, 938–952. 10.1002/lno.10262

  • 92

    SchileL. M.KauffmanJ. B.CrooksS.FourqureanJ. W.GlavanJ.MegonigalJ. P. (2016). Limits on carbon sequestration in arid blue carbon ecosystems. Ecol. Appl. 27, 859–874. 10.1002/eap.1489

  • 93

    SchmidtM. W. I.TornM. S.AbivenS.DittmarT.GuggenbergerG.JanssensI. A.et al. (2011). Persistence of soil organic matter as an ecosystem property. Nature478, 49–56. 10.1038/nature10386

  • 94

    SchuurE. A. G.CarboneM. S.Hicks PriesC. E.HopkinsF. M.NataliS. M. (2016). Radiocarbon in terrestrial systems, in Radiocarbon and Climate Change, eds SchuurE. A. G.DruffelE. R. M.TrumboreS. E. (Springer International Publishing), 167–220.

  • 95

    ScourseJ. D.WanamakerA. D.WeidmanC.HeinemeierJ.ReimerP. J.ButlerP. G.et al. (2012). The marine radiocarbon bomb pulse across the temperate North Atlantic: a compliation of Δ14C time histories from Arctica Islandica growth increments. Radiocarbon54, 165–186. 10.2458/azu_js_rc.v54i2.16026

  • 96

    SerranoO.LaveryP. S.DuarteC. M.KendrickG. A.CalafatA.YorkP. H.et al. (2016a). Can mud (silt and clay) concentration be used to predict soil organic carbon content within seagrass ecosystems?Biogeosciences13, 4915–4926. 10.5194/bg-13-4915-2016

  • 97

    SerranoO.LaveryP. S.López-MerinoL.BallesterosE.MateoM. Á. (2016b). Location and associated carbon storage of erosional escarpments of seagrass posidonia mats. Front. Mar. Sci.3:42. 10.3389/fmars.2016.00042

  • 98

    SerranoO.LaveryP. S.RozaimiM.MateoM. A. (2014). Influence of water depth on the carbon sequestration capacity of seagrasses. Global Biogeochem. Cycles28, 950–961. 10.1002/2014GB004872

  • 99

    SerranoO.MateoM. A.RenomP.JuliàR. (2012). Characterization of soils beneath a Posidonia oceanica meadow. Geoderma 185–186, 26–36. 10.1016/j.geoderma.2012.03.020

  • 100

    SerranoO.RicartA. M.LaveryP. S.MateoM. A.Arias-OrtizA.MasquéP.et al. (2015). Key biogeochemical factors affecting soil carbon storage in Posidoniameadows. Biogeosci. Discussions12, 18913–18944. 10.5194/bgd-12-18913-2015

  • 101

    SerranoO.RuhonR.LaveryP. S.KendrickG. A.HickeyS.MasquéP.et al. (2016c). Impact of mooring activities on carbon stocks in seagrass meadows. Sci. Rep.6:23193. 10.1038/srep23193

  • 102

    ShortF.CarruthersT.DennisonW.WaycottM. (2007). Global seagrass distribution and diversity: a bioregional model. J. Exp. Mar. Biol. Ecol.350, 3–20. 10.1016/j.jembe.2007.06.012

  • 103

    SimpsonM. J.SimpsonA. J. (2012). The chemical ecology of soil organic matter molecular constituents. J. Chem. Ecol.38, 768–784. 10.1007/s10886-012-0122-x

  • 104

    SixJ.BossuytH.DegryzeS.DenefK. (2004). A history of research on the link between (micro) aggregates, soil biota, and soil organic matter dynamics. Soil Tillage Res.79, 7–31. 10.1016/j.still.2004.03.008

  • 105

    SleutelS.CnuddeV.MasschaeleB.VlassenbroekJ.DierickM.Van HoorebekeL.et al. (2008). Comparison of different nano- and micro-focus X-ray computed tomography set-ups for the visualization of the soil microstructure and soil organic matter. Comput. Geosci.34, 931–938. 10.1016/j.cageo.2007.10.006

  • 106

    SollinsP.HomannP.CaldwellB. A. (1996). Stabilization and destabilization of soil organic matter: mechanisms and controls. Geoderma74, 1–41. 10.1016/S0016-7061(96)00036-5

  • 107

    SolomonD.LehmannJ.KinyangiJ.LiangB.SchaferT. (2004). Carbon K-Edge NEXAFS and FTIR-ATR spectroscopic investigation of organic carbon speciation in soils. Soil Sci. Soc. Am. J.69, 107–119. 10.2136/sssaj2005.0107dup

  • 108

    StuiverM.PearsonG. W.BraziunasT. F. (1986). Radiocarbon age calibration of marine samples back to 9000 cal yr BP. Radiocarbon28, 980–1021. 10.1017/S0033822200060264

  • 109

    ThurebornP.HuY. O. O.FranzettiA.SjölingS.LundinD. (2017). Accumulation of DNA in an anoxic sediment – rDNA and rRNA presence of members of the microbial community from Landsort Deep, the Baltic Sea. PeerJ5:e2051v2. 10.7287/peerj.preprints.2051v2

  • 110

    Tisnérat-LabordeN.MontagnaP.McCullochM.SianiG.SilenziS.FrankN. (2013). A high-resolution coral-based Δ14C record of surface water processes in the Western Mediterranean Sea. Radiocarbon55, 1617–1630. 10.1017/S0033822200048530

  • 111

    ToluJ.GerberL.BoilyJ.-F.BindlerR. (2015). High-throughput characterization of sediment organic matter by pyrolysis–gas chromatography/mass spectrometry and multivariate curve resolution: a promising analytical tool in (paleo)limnology. Anal. Chim. Acta880, 93–102. 10.1016/j.aca.2015.03.043

  • 112

    TornM. S.SwanstonC. W.CastanhaC.TrumboreS. E. (2009). Storage and turnover of organic matter in soil, in Biophysico-Chemical Processes Involving Natural Nonliving Organic Matter in Environmental Systems, eds SenesiN.XingB.HuangP. M. (Hoboken, NJ: John Wiley & Sons, Inc.), 219–272. 10.1002/9780470494950.ch6

  • 113

    TrumboreS. E. (1993). Comparison of carbon dynamics in tropical and temperate soils using radiocarbon measurements. Global Biogeochem. Cycles7, 275–290. 10.1029/93GB00468

  • 114

    TrumboreS. E. (2000). Age of soil organic matter and soil respiration: radiocarbon constraints on belowground C dynamics. Ecol. Appl.10, 399–411. 10.1890/1051-0761(2000)010[0399:AOSOMA]2.0.CO;2

  • 115

    TrumboreS. E. (2009). Radiocarbon and soil carbon dynamics. Annu. Rev. Earth Planet Sci.37, 47–66. 10.1146/annurev.earth.36.031207.124300

  • 116

    TrumboreS. E.HardenJ. W. (1997). Accumulation and turnover of carbon in organic and mineral soils of the BOREAS northern study area. J. Geophys. Res.102, 28817–28830. 10.1029/97JD02231

  • 117

    TrumboreS. E.SierraC. A.Hicks PriesC. E. (2016). Radiocarbon nomenclature, theory, models, and interpretation: measuring age, determining cycling rates, and tracing source pools, in Radiocarbon and Climate Change, eds SchuurE. A. G.DruffelE. R. M.TrumboreS. E. (Springer International Publishing), 45–82.

  • 118

    TrumboreS. E.ZhengS. (1996). Comparison of fractionation methods for soil organic matter 14C analysis. Radiocarbon38, 219–229. 10.1017/S0033822200017598

  • 119

    von LützowM.Kögel-KnabnerI.EkschmittK.FlessaH.GuggenbergerG.MatznerE.et al. (2007). SOM fractionation methods: relevance to functional pools and to stabilization mechanisms. Soil Biol. Biochem.39, 2183–2207. 10.1016/j.soilbio.2007.03.007

  • 120

    von MeringC.HugenholtzP.RaesJ.TringeS. G.DoerksT.JensenL. J.et al. (2007). Quantitative phylogenetic assessment of microbial communities in diverse environments. Science315, 1126–1130. 10.1126/science.1133420

  • 121

    van OortF.JongmansA. G.CiteauL.LamyI.ChevallierP. (2006). Microscale Zn and Pb distribution patterns in subsurface soil horizons: an indication for metal transport dynamics. Eur. J. Soil Sci.57, 154–166. 10.1111/j.1365-2389.2005.00725.x

  • 122

    VerchotL. V.DutaurL.ShepherdK. D.AlbrechtA. (2011). Organic matter stabilization in soil aggregates: understanding the biogeochemical mechanisms that determine the fate of carbon inputs in soils. Geoderma161, 182–193. 10.1016/j.geoderma.2010.12.017

  • 123

    VichkovittenT.HolmerM. (2005). Dissolved and particulate organic matter in contrasting Zostera marina (eelgrass) sediments. J. Exp. Mar. Biol. Ecol.6, e18311. 10.1016/j.jembe.2004.11.002

  • 124

    VinduskovaO.SebagD.CailleauG.BrusJ.FrouzJ. (2015). Methodological comparison for quantitative analysis of fossil and recently derived carbon in mine soils with high content of aliphatic kerogen. Org. Geochem. 89–90, 14–22. 10.1016/j.orggeochem.2015.10.001

  • 125

    WallensteinM. D.WeintraubM. N. (2008). Emerging tools for measuring and modeling the in situ activity of soil extracellular enzymes. Soil Biol. Biochem.40, 2098–2106. 10.1016/j.soilbio.2008.01.024

  • 126

    WaycottM.DuarteC. M.CarruthersT. J. B.OrthR. J.DennisonW. C.OlyarnikS.et al. (2009). Accelerating loss of seagrasses across the globe threatens coastal ecosystems. Proc. Natl. Acad. Sci.U.S.A.106, 12377–12381. 10.1073/pnas.0905620106

  • 127

    WebsterG.WattL. C.RinnaJ.FryJ. C.EvershedR. P.ParkesR. J.et al. (2006). A comparison of stable-isotope probing of DNA and phospholipid fatty acids to study prokaryotic functional diversity in sulfate-reducing marine sediment enrichment slurries. Environ. Microbiol.8, 1575–1589. 10.1111/j.1462-2920.2006.01048.x

  • 128

    WeidmanC. R.JonesG. A. (1993). A shell-derived time history of bomb 14C on Georges Bank and its Labrador Sea implications. J. Geophys. Res. Oceans98, 14577–14588. 10.1029/93JC00785

  • 129

    WernerU.BirdP.WildC.FerdelmanT.PolerechyL.EickertG.et al. (2006). Spatial patterns of aerobic and anaerobic mineralization rates and oxygen penetration dynamics in coral reef sediments. Mar. Ecol. Prog. Ser.309, 93–105. 10.3354/meps309093

  • 130

    WestM.EllisA. T.KregsamerP.PottsP. J.StreliC.VanhoofC.et al. (2007). Atomic spectrometry update. X-ray fluorescence spectrometry. J. Anal. Atmos. Spectrom.22, 1304–1329. 10.1039/b712079f

  • 131

    YuS. Y.ShenJ.ColmanS. M. (2007). Modeling the radiocarbon reservoir effect in lacustrine systems. Radiocarbon49, 1241–1254. 10.1017/S0033822200043150

Summary

Keywords

organic carbon, seagrass, residence times, state-factors, stabilization mechanisms

Citation

Belshe EF, Mateo MA, Gillis L, Zimmer M and Teichberg M (2017) Muddy Waters: Unintentional Consequences of Blue Carbon Research Obscure Our Understanding of Organic Carbon Dynamics in Seagrass Ecosystems. Front. Mar. Sci. 4:125. doi: 10.3389/fmars.2017.00125

Received

24 January 2017

Accepted

18 April 2017

Published

04 May 2017

Volume

4 - 2017

Edited by

Christian Grenz, Mediterranean Institute of Oceanography, France

Reviewed by

Jan Marcin Weslawski, Institute of Oceanology (PAN), Poland; Gerard Pergent, University of Corsica Pascal Paoli, France

Updates

Copyright

*Correspondence: E. Fay Belshe

This article was submitted to Marine Ecosystem Ecology, a section of the journal Frontiers in Marine Science

Disclaimer

All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.

Outline

Figures

Cite article

Copy to clipboard


Export citation file


Share article

Article metrics