您当前的位置: 首页 > 资源详细信息
资源基本信息 
来源机构: 《科学》
来源目录: News
发布日期: Feb 14, 2020
资源类型: 300.57KB
资源性质:
重要度:    
资源评价:

资源推荐:

Major role of particle fragmentation in regulating biological sequestration of CO2 by the oceans

Breaking up is easy to do.Sinking particles transport carbon to the seafloor, where they are buried in sediments and either provide food for benthic organisms or sequester the carbon they contain. However, only ∼30% of the maximum flux reaches depths of a kilometer. This loss cannot be fully accounted for by current measurements. Briggs et al. used data collected by robotic Biogeochemical-Argo floats to quantify total mesopelagic fragmentation and found that this process accounts for roughly half of the observed flux loss (see the Perspective by Nayak and Twardowski). Fragmentation is thus perhaps the most important process controlling the remineralization of sinking organic carbon.Science, this issue p. 791; see also p. 738.Abstract.A critical driver of the ocean carbon cycle is the downward flux of sinking organic particles, which acts to lower the atmospheric carbon dioxide concentration. This downward flux is reduced by more than 70% in the mesopelagic zone (100 to 1000 meters of depth), but this loss cannot be fully accounted for by current measurements. For decades, it has been hypothesized that the missing loss could be explained by the fragmentation of large aggregates into small particles, although data to test this hypothesis have been lacking. In this work, using robotic observations, we quantified total mesopelagic fragmentation during 34 high-flux events across multiple ocean regions and found that fragmentation accounted for 49 ± 22% of the observed flux loss. Therefore, fragmentation may be the primary process controlling the sequestration of sinking organic carbon.Large organic particles (>100 μm) sinking through the ocean’s mesopelagic zone (100 to 1000 m) play a critical role in regulating the global carbon cycle. These particles are part of the biological carbon pump, which transfers an estimated 5 to 12 Pg of C per year (1–3) from the sunlit ocean and sequesters 15 to 30% of this carbon for centuries to millennia in the deep ocean (4–6). The organic carbon that is sequestered directly affects atmospheric CO2 concentrations (7). Sinking organic carbon is also a primary source of energy for ocean ecosystems in and below the mesopelagic zone and is essential to the ecosystem services they provide (8, 9).Despite its importance, we still lack a quantitative, mechanistic understanding of key parts of the biological carbon pump. Particularly, we poorly understand the subsurface loss processes that determine the depth at which sinking organic carbon is remineralized to CO2. This depth affects, in turn, long-term atmospheric CO2 sequestration (7). Measurements of sinking particle flux at different depths via underwater sediment traps, radioactive particle tracers, and underwater cameras indicate that, on average, ~70 to 85% of sinking carbon flux is lost in the mesopelagic (4–6). However, direct consumption of fast-sinking particles, either by attached bacteria (10–12) or by zooplankton (13), appears to explain less than half of this observed flux attenuation. The remaining ≥50% of the observed mesopelagic flux attenuation might be explained by fragmentation into smaller, slower-sinking particles (12). This would be consistent with the observed seasonal buildup of small particles in the mesopelagic zone (14) and the metabolic activities of free-living bacteria that consume such particles (13). Fragmentation rates have been estimated more directly, in both the laboratory and the upper ocean, from changes in particle size and have been attributed to several mechanisms. Microbial degradation has been shown to fragment marine particles in the laboratory (15, 16), marine particle fragmentation by zooplankton feeding has been observed both in the laboratory (17) and in the upper ocean (18), and fragmentation caused by ocean turbulence has been proposed to explain patterns of particle size in the mixed layer (19, 20). In the mesopelagic zone, however, similar studies have not been practical. As a consequence, the hypothesis that fragmentation can reconcile existing measurements of the mesopelagic carbon budget has not been rigorously tested. To address this, we have estimated fragmentation rates at broad scale by simultaneously tracking changes in large (21) and small (14) mesopelagic particle concentrations using optical data collected by Biogeochemical-Argo floats.We analyzed data from 25 floats deployed across the subpolar North Atlantic and the Atlantic and Indian sectors of the Southern Ocean between 2013 and 2016 (Fig. 1). All floats carried sensors for particulate optical backscattering (bbp), a proxy for particulate mass concentration (22), and for chlorophyll a fluorescence (F), a proxy for live phytoplankton biomass (23) (see table S1 for full list of abbreviations used in this manuscript). Floats were profiled to 1000 m with temporal and vertical resolutions of 2 to 3 days and 1 m, respectively, during spring and summer phytoplankton blooms. F and bbp were each divided into three components (fig. S1) [as described in (24)]: deep sensor blanks, including a background of small refractory particles (bbr and Fr); small, labile backscattering (bbs) and fluorescing (Fs) particles; and large, fast-sinking backscattering (bbl) and fluorescing (Fl) particles. The division between small and large corresponds roughly to a particle diameter of 100 μm for bbs versus bbl and a particle chlorophyll content of 60 pg for Fs versus Fl (24). We attribute Fl primarily to live phytoplankton aggregates; Fl represents a subset of bbl, which additionally includes fecal and detrital matter (21). Between May 2013 and February 2018, we identified 34 pulses of bbl and/or Fl in the mesopelagic that were associated with surface phytoplankton blooms and were clearly distinguishable from prebloom background concentrations. Bulk large-particle sinking velocity was estimated for each large-particle pulse (fig. S2) from the timing of peak concentration versus depth (24). Mean sinking velocities (and 95% confidence intervals) across all pulses were 74 (58 to 100) m per day for large backscattering particles and 98 (79 to 129) m per day for large fluorescing particles. Download high-res image . Open in new tab . Download Powerpoint . Fig. 1 Location of particle-flux pulses. Gray circles represent the 34 pulses analyzed in this study. Darker grays indicate overlapping circles. Magenta circles indicate example pulses shown in Fig. 2. The background is a map of climatological mean surface chlorophyll concentration from MODIS-Aqua (2002 to 2017). We observed close coupling between large- and small-particle concentrations during these flux pulses (Fig. 2). Small-particle concentrations increased rapidly during periods of peak large-particle concentration (Fig. 2; solid black lines) at all depths below 200 m, peaking slightly later (e.g., Fig. 2, left column: peak Fs lags behind peak Fl by ~2 days, regardless of depth). This coupling provides strong evidence that large-particle fragmentation drives the observed accumulation of small particles in the mesopelagic, both for large particles in general (bbl) and phytoplankton aggregates in particular (Fl). Download high-res image . Open in new tab . Download Powerpoint . Fig. 2 Fragmentation of large particles generates small particles at depth. Large- and small-particle measurements from example large-particle pulses from the North Atlantic (left panels) and the Southern Ocean (right panels) are shown. Large-particle fluorescence Fl (green circles) and large-particle backscattering bbl (red circles) are shown above the corresponding log10 small-particle fluorescence Fs (green) and backscattering bbs (red). Large-particle measurements are plotted individually with higher values (darker colors) covering lower values. Thin black lines along the top edges of the panels show mixed-layer depth; thick, diagonal solid lines show linear least-squares fits of maximum large-particle concentration with depth; and dashed lines show the ±15 day windows used for fragmentation calculations. Similar visualizations for all 34 plumes in this study can be found at seanoe.org (26). Chl, chorophyll. We quantified specific fragmentation rates during each sinking pulse by tracking these changes in the concentrations of large and small particles as a function of depth and time. Full computations, assumptions, and uncertainty budgets (24) are shown in figs. S3 to S11 along with alternative calculations supporting key methodological assumptions (figs. S11 to S13). Mean fragmentation rate profiles across all pulses varied with depth and particle type from 0.03 to 0.27 per day (Fig. 3). Although wide uncertainty bounds prevent firm conclusions, the patterns in these rates offer preliminary indications of possible fragmentation mechanisms. First, live phytoplankton aggregates (Fl) fragmented at higher rates than large sinking particles in general (bbl) at all depths in the mesopelagic zone (Fig. 3). Fresh phytoplankton aggregates therefore appear either more fragile than other large sinking particles and/or are subject to higher local shear. The latter might result from selective feeding on fresh material by zooplankton. Second, specific fragmentation rates decreased with depth (Fig. 3). This depth dependency could result from passive breakup of more fragile particles closer to the surface. It might also result from higher zooplankton activity closer to the surface, where we expect food to be more abundant and more nutritious. On average, fragmentation accounted for close to 50% of the observed loss rates of large particles in general and 30 to 60% of the loss of large fluorescing particles (Fig. 3) at all depths between 250 and 950 m. Download high-res image . Open in new tab . Download Powerpoint . Fig. 3 Fragmentation contributes 50% of the observed flux attenuation. First and third panels from left show mean specific fragmentation rates of large particles bbl (red) and of large fluorescing particles Fl (green) across all large-particle pulses. Second and fourth panels from left show the mean fraction of bbl flux attenuation (red) and Fl flux attenuation (green) explained by this fragmentation. Shaded areas show 95% confidence intervals. Black curves and equations in first and third panels show least-squared exponential fits of specific fragmentation rates versus depth. d, day; r2, coefficient of determination; x, specific fragmentation rate (per day); y, depth (m). We also found regional differences in specific fragmentation rates. When calculated using the same parameterizations (24), large-particle (bbl) specific fragmentation rates were notably higher in the Southern Ocean than those in the North Atlantic, between 250 and 600 m (Fig. 4, left panel). On the other hand, fragmentation of fresh phytoplankton aggregates (Fl) was not different in the two regions (Fig. 4, right panel). Further differences in bbl fragmentation were observed between subregions of the Southern Ocean (table S2). Investigation of these regional differences may help to constrain the drivers of fragmentation. Download high-res image . Open in new tab . Download Powerpoint . Fig. 4 Regional differences in fragmentation. Comparison between mean specific fragmentation rates of large particles bbl (left) and those of large fluorescing particles Fl (right) during North Atlantic (purple) and Southern Ocean (blue) phytoplankton blooms. Bold lines show means and shaded areas show two standard errors around the means. Our measurements provide quantitative and geographically broad support for the hypothesis that fragmentation exerts a major control on mesopelagic carbon flux (12), which has two notable implications. First, when added to previous estimates of large-particle consumption by zooplankton and bacteria (13), fragmentation can now fully explain the observed flux attenuation at high latitudes. Therefore, these results strengthen our mechanistic understanding of the biological carbon pump. Second, our results imply that fragmentation may be the single most important process in determining the depth at which fast-sinking organic carbon is remineralized. By extension, fragmentation appears to be a key regulator of atmospheric CO2 concentrations (7) and of the delivery of energy to deep-ocean ecosystems versus its retention in mesopelagic ecosystems (25).Supplementary Materials.science.sciencemag.org/content/367/6479/791/suppl/DC1Materials and MethodsFigs. S1 to S13Tables S1 and S2References (27–34)http://www.sciencemag.org/about/science-licenses-journal-article-reuse This is an article distributed under the terms of the Science Journals Default License.References and Notes.↵ P. W. Boyd , . T. W. Trull ., Understanding the export of biogenic particles in oceanic waters: Is there consensus? Prog. Oceanogr. 72 , 276 –312 (2007 ). doi: 10.1016/j.pocean.2006.10.007 OpenUrl CrossRef Web of Science S. A. Henson , . R. Sanders , . E. Madsen , . P. J. Morris , . F. Le Moigne , . G. D. Quartly ., A reduced estimate of the strength of the ocean’s biological carbon pump . Geophys. Res. Lett. 38 , L04606 (2011 ). doi: 10.1029/2011GL046735 OpenUrl CrossRef ↵ D. A. Siegel , . K. O. Buesseler , . S. C. Doney , . S. F. Sailley , . M. J. Behrenfeld , . P. W. Boyd ., Global assessment of ocean carbon export by combining satellite observations and food-web models . Global Biogeochem. Cycles 28 , 181 –196 (2014 ). doi: 10.1002/2013GB004743 OpenUrl CrossRef Web of Science ↵ J. H. Martin , . G. A. Knauer , . D. M. Karl , . W. W. Broenkow ., VERTEX: carbon cycling in the northeast Pacific . Deep Sea Res. Part A Oceanogr. Res. Pap. 34 , 267 –285 (1987 ). doi: 10.1016/0198-0149(87)90086-0 OpenUrl CrossRef Web of Science L. Guidi , . L. Legendre , . G. Reygondeau , . J. Uitz , . L. Stemmann , . S. A. Henson ., A new look at ocean carbon remineralization for estimating deepwater sequestration . Global Biogeochem. Cycles 29 , 1044 –1059 (2015 ). doi: 10.1002/2014GB005063 OpenUrl CrossRef ↵ S. A. Henson , . R. Sanders , . E. Madsen ., Global patterns in efficiency of particulate organic carbon export and transfer to the deep ocean . Global Biogeochem. Cycles 26 , GB1028 (2012 ). doi: 10.1029/2011GB004099 OpenUrl CrossRef ↵ E. Y. Kwon , . F. Primeau , . J. L. Sarmiento ., The impact of remineralization depth on the air-sea carbon balance . Nat. Geosci. 2 , 630 –635 (2009 ). doi: 10.1038/ngeo612 OpenUrl CrossRef ↵ X. Irigoien , . T. A. Klevjer , . A. Røstad , . U. Martinez , . G. Boyra , . J. L. Acuña , . A. Bode , . F. Echevarria , . J. I. Gonzalez-Gordillo , . S. Hernandez-Leon , . S. Agusti , . D. L. Aksnes , . C. M. Duarte , . S. Kaartvedt ., Large mesopelagic fishes biomass and trophic efficiency in the open ocean . Nat. Commun. 5 , 3271 (2014 ). doi: 10.1038/ncomms4271 pmid: 24509953 OpenUrl CrossRef PubMed ↵ M. A. St. John , . A. Borja , . G. Chust , . M. Heath , . I. Grigorov , . P. Mariani , . A. P. Martin , . R. S. Santos ., A Dark Hole in Our Understanding of Marine Ecosystems and Their Services: Perspectives from the Mesopelagic Community . Front. Mar. Sci. 3 , 31 (2016 ). doi: 10.3389/fmars.2016.00031 OpenUrl CrossRef ↵ J. R. Collins , . B. R. Edwards , . K. Thamatrakoln , . J. E. Ossolinski , . G. R. DiTullio , . K. D. Bidle , . S. C. Doney , . B. A. S. Van Mooy ., The multiple fates of sinking particles in the North Atlantic Ocean . Global Biogeochem. Cycles 29 , 1471 –1494 (2015 ). doi: 10.1002/2014GB005037 OpenUrl CrossRef A. Belcher , . M. Iversen , . S. Giering , . V. Riou , . S. A. Henson , . L. Berline , . L. Guilloux , . R. Sanders ., Depth-resolved particle-associated microbial respiration in the northeast Atlantic . Biogeosciences 13 , 4927 –4943 (2016 ). doi: 10.5194/bg-13-4927-2016 OpenUrl CrossRef ↵ D. M. Karl , . G. A. Knauer , . J. H. Martin ., Downward flux of particulate organic matter in the ocean: A particle decomposition paradox . Nature 332 , 438 –441 (1988 ). doi: 10.1038/332438a0 OpenUrl CrossRef Web of Science ↵ S. L. C. Giering , . R. Sanders , . R. S. Lampitt , . T. R. Anderson , . C. Tamburini , . M. Boutrif , . M. V. Zubkov , . C. M. Marsay , . S. A. Henson , . K. Saw , . K. Cook , . D. J. Mayor ., Reconciliation of the carbon budget in the ocean’s twilight zone . Nature 507 , 480 –483 (2014 ). doi: 10.1038/nature13123 pmid: 24670767 OpenUrl CrossRef PubMed Web of Science ↵ G. Dall’Olmo , . K. A. Mork ., Carbon export by small particles in the Norwegian Sea . Geophys. Res. Lett. 41 , 2921 –2927 (2014 ). doi: 10.1002/2014GL059244 OpenUrl CrossRef Web of Science ↵ L. R. Pomeroy , . D. Deibel ., Aggregation of Organic Matter By Pelagic Tunicates . Limnol. Oceanogr. 25 , 643 –652 (1980 ). doi: 10.4319/lo.1980.25.4.0643 OpenUrl CrossRef ↵ B. A. Biddanda , . L. R. Pomeroy ., Microbial aggregation and degradation of phytoplankton-derived detritus in seawater. I. Microbial succession . Mar. Ecol. Prog. Ser. 42 , 79 –88 (1988 ). doi: 10.3354/meps042079 OpenUrl CrossRef Web of Science ↵ S. Goldthwait , . J. Yen , . J. Brown , . A. Alldredge ., Quantification of marine snow fragmentation by swimming euphausiids . Limnol. Oceanogr. 49 , 940 –952 (2004 ). doi: 10.4319/lo.2004.49.4.0940 OpenUrl CrossRef ↵ L. Dilling , . A. L. Alldredge ., Fragmentation of marine snow by swimming macrozooplankton : A new process impacting carbon cycling in the sea . Deep Sea Res. Part I Oceanogr. Res. Pap. 47 , 1227 –1245 (2000 ). doi: 10.1016/S0967-0637(99)00105-3 OpenUrl CrossRef ↵ G. A. Jackson ., Comparing Observed Changes in Particle-Size Spectra with Those Predicted Using Coagulation Theory . Deep Sea Res. Part II Topical Stud. Oceanogr. 42 , 159 –184 (1995 ). doi: 10.1016/0967-0645(95)00010-N OpenUrl CrossRef ↵ J. Ruiz ., What generates daily cycles of marine snow? Deep Sea Res. Part I Oceanogr. Res. Pap. 44 , 1105 –1126 (1997 ). doi: 10.1016/S0967-0637(97)00012-5 OpenUrl CrossRef ↵ N. Briggs , . M. J. Perry , . I. Cetinić , . C. Lee , . E. D’Asaro , . A. M. Gray , . E. Rehm ., High-resolution observations of aggregate flux during a sub-polar North Atlantic spring bloom . Deep Sea Res. Part I Oceanogr. Res. Pap. 58 , 1031 –1039 (2011 ). doi: 10.1016/j.dsr.2011.07.007 OpenUrl CrossRef ↵ R. A. Reynolds , . D. Stramski , . G. Neukermans ., Optical backscattering by particles in Arctic seawater and relationships to particle mass concentration, size distribution, and bulk composition . Limnol. Oceanogr. 61 , 1869 –1890 (2016 ). doi: 10.1002/lno.10341 OpenUrl CrossRef ↵ C. Roesler , . J. Uitz , . H. Claustre , . E. Boss , . X. Xing , . E. Organelli , . N. Briggs , . A. Bricaud , . C. Schmechtig , . A. Poteau , . F. D’Ortenzio , . J. Ras , . S. Drapeau , . N. Haëntjens , . M. Barbieux ., Recommendations for obtaining unbiased chlorophyll estimates from in situ chlorophyll fluorometers: A global analysis of WET Labs ECO sensors . Limnol. Oceanogr. Methods 15 , 572 –585 (2017 ). doi: 10.1002/lom3.10185 OpenUrl CrossRef ↵See supplementary materials. .↵ D. J. Mayor , . R. Sanders , . S. L. C. Giering , . T. R. Anderson ., Microbial gardening in the ocean’s twilight zone: detritivorous metazoans benefit from fragmenting, rather than ingesting, sinking detritus . BioEssays 36 , 1132 –1137 (2014 ). doi: 10.1002/bies.201400100 pmid: 25220362 OpenUrl CrossRef PubMed ↵N. Briggs, G. Dall’Olmo, H. Claustre, Size-fractionated optical backscattering and chlorophyll fluorescence from 34 high-latitude phytoplankton blooms. SEANOE (2019); https://doi.org/10.17882/70484.doi: 10.17882/70484 OpenUrl CrossRef PubMed ↵ X. Zhang , . L. Hu , . M. X. He ., Scattering by pure seawater: Effect of salinity . Opt. Express 17 , 5698 –5710 (2009 ). doi: 10.1364/OE.17.005698 pmid: 19333338 OpenUrl CrossRef PubMed J. M. Sullivan, M. S. Twardowski, J. Ronald, V. Zaneveld, C. C. Moore, in Light Scattering Reviews 7, A. A. Kokhanovsky, Ed. (Springer, 2013), pp. 189–224. N. T. Briggs , . W. H. Slade , . E. Boss , . M. J. Perry ., Method for estimating mean particle size from high-frequency fluctuations in beam attenuation or scattering measurements . Appl. Opt. 52 , 6710 –6725 (2013 ). doi: 10.1364/AO.52.006710 pmid: 24085170 OpenUrl CrossRef PubMed W. M. Berelson ., The Flux of Particulate Organic Carbon Into the Ocean Interior: A Comparison of Four U.S. JGOFS Regional Studies . Oceanography 14 , 59 –67 (2001 ). doi: 10.5670/oceanog.2001.07 OpenUrl CrossRef A. Waite , . A. Fisher , . P. A. Thompson , . P. J. Harrison ., Sinking rate versus cell volume relationships illuminate sinking rate control mechanisms in marine diatoms . Mar. Ecol. Prog. Ser. 157 , 97 –108 (1997 ). doi: 10.3354/meps157097 OpenUrl CrossRef X. Y. Li , . B. E. Logan ., Size distributions and fractal properties of particles during a sumulated phytoplankton bloom in a mesocosm . Deep Sea Res. Part II Topical Stud. Oceanogr. 42 , 125 –138 (1995 ). doi: 10.1016/0967-0645(95)00008-E OpenUrl CrossRef A. Hatcher , . P. Hill , . J. Grant ., Optical backscatter of marine flocs . J. Sea Res. 46 , 1 –12 (2001 ). doi: 10.1016/S1385-1101(01)00066-1 OpenUrl CrossRef ↵ E. N. Flory , . P. S. Hill , . T. G. Milligan , . J. Grant ., The relationship between floc area and backscatter during a spring phytoplankton bloom . Deep Sea Res. Part I Oceanogr. Res. Pap. 51 , 213 –223 (2004 ). doi: 10.1016/j.dsr.2003.09.012 OpenUrl CrossRef Acknowledgments: We thank the entire international Argo community for its work over decades to create a reliable global profiling float network and its recent work to integrate biogeochemical sensors into this network. We especially thank A. Poteau for his development and continuous support of float control and visualization tools used to adapt float vertical and temporal sampling resolutions to the present study requirements. We also thank two anonymous reviewers for their thorough and insightful comments, which led to substantial improvements to this manuscript. Funding: The collection of the data used in this manuscript was funded by a European Research Council Advanced grant (remOcean, agreement no. 246577) as well as the climate initiative of the BNP Paribas foundation (SOCLIM project), French LEFE- GMMC, and UK BioArgo projects. Analysis was funded by U.S. National Science Foundation Postdoctoral Research Fellowship OCE1420929. Final writing was funded by a European Research Council Consolidator grant (GOCART, agreement no. 724416) and a European Research Council Advanced grant (REFINE, agreement no. 834177). Author contributions: N.B. and G.D. conceptualized the study. N.B. developed the methods, and H.C. managed the data collection to optimize for these methods. N.B. carried out all data analysis, including software development, with periodic feedback from G.D. and H.C. N.B wrote the original draft and generated all figures. N.B., G.D., and H.C. reviewed and edited the final manuscript. Competing interests: The authors declare no competing interests. Data and materials availability: All data used in this study are available from the Argo Global Data Assembly Centers in Brest, France (ftp://ftp.ifremer.fr/ifremer/argo/dac/coriolis) and Monterey, California (ftp://usgodae.org/pub/outgoing/argo/dac/coriolis), in subfolders with names corresponding to the WMO numbers of individual floats given in table S2 of the supplemental methods. Intermediate (binned) data products used in this study are available at seanoe.org (26), along with data processing visualizations for all 34 plumes.

原始网站图片
 增加监测目标对象/主题,请 登录 直接在原文中划词!