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  • 1
    Publication Date: 2024-02-07
    Description: In this study, we provide a method to quantify the uncertainty associated with sampling particle size distributions (PSD), using a global compilation of Underwater Vision Profiler observations (UVP, version 5). The UVP provides abundant in situ data of the marine PSD on global scales and has been used for a diversity of applications, but the uncertainty associated with its measurements has not been quantified, including how this uncertainty propagates into derived products of interest. We model UVP sampling uncertainty using Bayesian Poisson statistics and provide formulae for the uncertainty associated with a given sampling volume and observed particle count. We also model PSD observations using a truncated power law to better match the low concentration associated with rare large particles as seen by the UVP. We use the two shape parameters from this statistical model to describe changes in the PSD shape across latitude band, season, and depth. The UVP sampling uncertainty propagates into an uncertainty for modeled carbon flux exceeding 50%. The statistical model is used to extend the size interval used in a PSD-derived carbon flux model, revealing a high sensitivity of the PSD-derived flux model to the inclusion of small particles (80–128 μm). We provide avenues to address additional uncertainties associated with UVP-derived carbon flux calculations.
    Type: Article , PeerReviewed
    Format: text
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  • 2
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    American Physical Society
    Publication Date: 2022-05-25
    Description: © The Author(s), 2015. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Physical Review E Statistical, Nonlinear, and Soft Matter Physics 92 (2015): 052128, doi: 10.1103/PhysRevE.92.052128.
    Description: Studies over the past decade have reported power-law distributions for the areas of terrestrial lakes and Arctic melt ponds, as well as fractal relationships between their areas and coastlines. Here we report similar fractal structure of ponds in a tidal flat, thereby extending the spatial and temporal scales on which such phenomena have been observed in geophysical systems. Images taken during low tide of a tidal flat in Damariscotta, Maine, reveal a well-resolved power-law distribution of pond sizes over three orders of magnitude with a consistent fractal area-perimeter relationship. The data are consistent with the predictions of percolation theory for unscreened perimeters and scale-free cluster size distributions and are robust to alterations of the image processing procedure. The small spatial and temporal scales of these data suggest this easily observable system may serve as a useful model for investigating the evolution of pond geometries, while emphasizing the generality of fractal behavior in geophysical surfaces.
    Description: This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under Grant No. 2388357, the Gordon and Betty Moore Foundation, and the National Science Foundation, Award No. OCE-1315201.
    Repository Name: Woods Hole Open Access Server
    Type: Article
    Format: application/pdf
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  • 3
    Publication Date: 2022-05-25
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Global Biogeochemical Cycles 32 (2018): 954-970, doi:10.1029/2017GB005797.
    Description: We describe the basis of a theory for interpreting measurements of two key biogeochemical fluxes—primary production by phytoplankton (p, μg C · L−1 · day−1) and biological carbon export from the surface ocean by sinking particles (f, mg C · m−2 · day−1)—in terms of their probability distributions. Given that p and f are mechanistically linked but variable and effectively measured on different scales, we hypothesize that a quantitative relationship emerges between collections of the two measurements. Motivated by the many subprocesses driving production and export, we take as a null model that large‐scale distributions of p and f are lognormal. We then show that compilations of p and f measurements are consistent with this hypothesis. The compilation of p measurements is extensive enough to subregion by biome, basin, depth, or season; these subsets are also well described by lognormals, whose log‐moments sort predictably. Informed by the lognormality of both p and f we infer a statistical scaling relationship between the two quantities and derive a linear relationship between the log‐moments of their distributions. We find agreement between two independent estimates of the slope and intercept of this line and show that the distribution of f measurements is consistent with predictions made from the moments of the p distribution. These results illustrate the utility of a distributional approach to biogeochemical fluxes. We close by describing potential uses and challenges for the further development of such an approach.
    Description: National Science Foundation Grant Number: OCE-1315201; Simons Foundation Grant Numbers: 329108, 553242; National Aeronautics and Space Administration Grant Numbers: NNX16AR47G, NNX16AR49G
    Keywords: Primary production ; Carbon export ; Export flux ; Lognormal distribution ; Scaling relationship ; Carbon cycle
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 4
    Publication Date: 2022-05-25
    Description: Author Posting. © American Geophysical Union, 2018. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Global Biogeochemical Cycles 32 (2018): 1312-1328, doi:10.1029/2018GB005934.
    Description: Ocean biological processes mediate the transport of roughly 10 petagrams of carbon from the surface to the deep ocean each year and thus play an important role in the global carbon cycle. Even so, the globally integrated rate of carbon export out of the surface ocean remains highly uncertain. Quantifying the processes underlying this biological carbon export requires a synthesis between model predictions and available observations of particulate organic carbon (POC) flux; yet the scale dissimilarities between models and observations make this synthesis difficult. Here we compare carbon export predictions from a mechanistic model with observations of POC fluxes from several data sets compiled from the literature spanning different space, time, and depth scales as well as using different observational methodologies. We optimize model parameters to provide the best match between model‐predicted and observed POC fluxes, explicitly accounting for sources of error associated with each data set. Model‐predicted globally integrated values of POC flux at the base of the euphotic layer range from 3.8 to 5.5 Pg C/year, depending on the data set used to optimize the model. Modeled carbon export pathways also vary depending on the data set used to optimize the model, as well as the satellite net primary production data product used to drive the model. These findings highlight the importance of collecting field data that average over the substantial natural temporal and spatial variability in carbon export fluxes, and advancing satellite algorithms for ocean net primary production, in order to improve predictions of biological carbon export.
    Description: NASA Ocean Biology and Biogeochemistry Program Grant Numbers: NNX16AR49G, NNXA122G, NNX16AR47G, OBB16_2‐0031; National Science Foundation
    Description: 2019-03-13
    Keywords: Carbon flux ; Remote sensing ; Carbon cycle ; Mechanistic model ; Optimization
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 5
    Publication Date: 2022-10-26
    Description: © The Author(s), 2018. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cael, B. B., & Bisson, K. (2018). Particle flux parameterizations: Quantitative and mechanistic similarities and differences. Frontiers in Marine Science, 5, (2018): 395. doi:10.3389/fmars.2018.00395.
    Description: The depth-attenuation of sinking particulate organic carbon (POC) is of particular importance for the ocean's role in the global carbon cycle. Numerous idealized flux-vs.-depth relationships are available to parameterize this process in Earth System Models. Here we show that these relationships are statistically indistinguishable from available POC flux profile data. Despite their quantitative similarity, we also show these relationships have very different implications for the flux leaving the upper ocean, as well as for the mechanisms governing POC flux. We discuss how this tension might be addressed both observationally and in modeling studies.
    Description: The National Aeronautics and Space Administration supported this work (awards NNX16AR47G and NNX16AR49G).
    Keywords: Carbon export ; Martin curve ; Carbon cycle ; Remineralization depth ; Particulate organic matter
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 6
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Cael, B. B., Bisson, K., Conte, M., Duret, M. T., Follett, C. L., Henson, S. A., Honda, M. C., Iversen, M. H., Karl, D. M., Lampitt, R. S., Mouw, C. B., Muller-Karger, F., Pebody, C. A., Smith, K. L., & Talmy, D. Open ocean particle flux variability from surface to seafloor. Geophysical Research Letters, 48(9), (2021): e2021GL092895, https://doi.org/10.1029/2021GL092895.
    Description: The sinking of carbon fixed via net primary production (NPP) into the ocean interior is an important part of marine biogeochemical cycles. NPP measurements follow a log-normal probability distribution, meaning NPP variations can be simply described by two parameters despite NPP's complexity. By analyzing a global database of open ocean particle fluxes, we show that this log-normal probability distribution propagates into the variations of near-seafloor fluxes of particulate organic carbon (POC), calcium carbonate, and opal. Deep-sea particle fluxes at subtropical and temperate time-series sites follow the same log-normal probability distribution, strongly suggesting the log-normal description is robust and applies on multiple scales. This log-normality implies that 29% of the highest measurements are responsible for 71% of the total near-seafloor POC flux. We discuss possible causes for the dampening of variability from NPP to deep-sea POC flux, and present an updated relationship predicting POC flux from mineral flux and depth.
    Description: B. B. Cael and S. A. Henson acknowledge support from the National Environmental Research Council (NE/R015953/1) and the Horizon 2020 Framework Programme (820989, project COMFORT). The work reflects only the authors' views; the European Commission and their executive agency are not responsible for any use that may be made of the information the work contains. S. A. Henson also acknowledges support from a European Research Council Consolidator grant (GOCART, agreement number 724416). C. L. Follett acknowledges support from the Simons Foundation (grants #827829 and #553242). M. H. Iversen acknowledges support from the DFG-Research Center/Cluster of Excellence “The Ocean Floor – Earth's Uncharted Interface”: EXC-2077-390741603 and the HGF Young Investigator Group SeaPump “Seasonal and regional food web interactions with the biological pump”: VH-NG-1000. M. C. Honda acknowledges financial support from the Ministry of Education, Culture, Sports, Science, and Technology – Japan (grants #: KAKENHI JP18H04144 and JP19H05667). M. Conte acknowledges support from the US National Science Foundation, Division of Ocean Sciences for support for the Oceanic Flux Program time-series since inception, most recently by NSF OCE grant 1829885. D. M. Karl acknowledges support from the Gordon and Betty Moore Foundation (#3794) and the Simons Foundation (SCOPE #329108).
    Keywords: Ballast ; bathypelagic ; biogeochemistry ; log-normal ; particle flux ; variability
    Repository Name: Woods Hole Open Access Server
    Type: Article
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  • 7
    Publication Date: 2022-08-15
    Description: The sinking of carbon fixed via net primary production (NPP) into the ocean interior is an important part of marine biogeochemical cycles. NPP measurements follow a log-normal probability distribution, meaning NPP variations can be simply described by two parameters despite NPP's complexity. By analyzing a global database of open ocean particle fluxes, we show that this log-normal probability distribution propagates into the variations of near-seafloor fluxes of particulate organic carbon (POC), calcium carbonate, and opal. Deep-sea particle fluxes at subtropical and temperate time-series sites follow the same log-normal probability distribution, strongly suggesting the log-normal description is robust and applies on multiple scales. This log-normality implies that 29% of the highest measurements are responsible for 71% of the total near-seafloor POC flux. We discuss possible causes for the dampening of variability from NPP to deep-sea POC flux, and present an updated relationship predicting POC flux from mineral flux and depth.
    Repository Name: EPIC Alfred Wegener Institut
    Type: Article , NonPeerReviewed
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  • 8
    Publication Date: 2022-05-27
    Description: © The Author(s), 2021. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Siegel, D. A., Cetinic, I., Graff, J. R., Lee, C. M., Nelson, N., Perry, M. J., Ramos, I. S., Steinberg, D. K., Buesseler, K., Hamme, R., Fassbender, A. J., Nicholson, D., Omand, M. M., Robert, M., Thompson, A., Amaral, V., Behrenfeld, M., Benitez-Nelson, C., Bisson, K., Boss, E., Boyd, P. W., Brzezinski, M., Buck, K., Burd, A., Burns, S., Caprara, S., Carlson, C., Cassar, N., Close, H. H., D’Asaro, E., Durkin, C., Erickson, Z., Estapa, M. L., Fields, E., Fox, J., Freeman, S., Gifford, S., Gong, W., Gray, D., Guidi, L., Haëntjens, N., Halsey, K., Huot, Y., Hansell, D., Jenkins, B., Karp-Boss, L., Kramer, S., Lam, P., Lee, J-M., Maas, A., Marchal, O., Marchetti, A., McDonnell, A., McNair, H., Menden-Deuer, S., Morison, F., Niebergall, A. K., Passow, U., Popp, B., Potvin, G., Resplandy, L., Roca-Martí, M., Roesler, C., Rynearson, T., Traylor, S., Santoro, A., Seraphin, K. D., Sosik, H. M., Stamieszkin, K., Stephens, B., Tang, W., Van Mooy, B., Xiong, Y., Zhang, X. An operational overview of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) Northeast Pacific field deployment. Elementa: Science of the Anthropocene, 9(1), (2021): 1, https://doi.org/10.1525/elementa.2020.00107.
    Description: The goal of the EXport Processes in the Ocean from RemoTe Sensing (EXPORTS) field campaign is to develop a predictive understanding of the export, fate, and carbon cycle impacts of global ocean net primary production. To accomplish this goal, observations of export flux pathways, plankton community composition, food web processes, and optical, physical, and biogeochemical (BGC) properties are needed over a range of ecosystem states. Here we introduce the first EXPORTS field deployment to Ocean Station Papa in the Northeast Pacific Ocean during summer of 2018, providing context for other papers in this special collection. The experiment was conducted with two ships: a Process Ship, focused on ecological rates, BGC fluxes, temporal changes in food web, and BGC and optical properties, that followed an instrumented Lagrangian float; and a Survey Ship that sampled BGC and optical properties in spatial patterns around the Process Ship. An array of autonomous underwater assets provided measurements over a range of spatial and temporal scales, and partnering programs and remote sensing observations provided additional observational context. The oceanographic setting was typical of late-summer conditions at Ocean Station Papa: a shallow mixed layer, strong vertical and weak horizontal gradients in hydrographic properties, sluggish sub-inertial currents, elevated macronutrient concentrations and low phytoplankton abundances. Although nutrient concentrations were consistent with previous observations, mixed layer chlorophyll was lower than typically observed, resulting in a deeper euphotic zone. Analyses of surface layer temperature and salinity found three distinct surface water types, allowing for diagnosis of whether observed changes were spatial or temporal. The 2018 EXPORTS field deployment is among the most comprehensive biological pump studies ever conducted. A second deployment to the North Atlantic Ocean occurred in spring 2021, which will be followed by focused work on data synthesis and modeling using the entire EXPORTS data set.
    Description: DAS, NN, KB, EF, SK, AB, AM, UP: NASA 80NSSC17K0692. MJB, EB, JG, LG, KH, LKB, JF, NH: NASA 80NSSC17K0568. KB, CBN, LR, MRM: NASA 80NSSC17K0555. CC, DH, BS: NASA 80NSSC18K0437. HC: NSF 1830016. BP, KDS: NSF 1829425. ME, KB, CD, MO: NASA 80NSSC17K0662. AF: NSF 1756932. BJ, KB, MB, SB, SC: NSF 1756442. PH, OM, JML: NSF 1829614. CL, ED, DN, MO, MJP, AT, ZN, ST: NASA 80NSSC17K0663. AM, NC, SG, WT, AN, WG: NASA 80NSSC17K0552. SMD, TR, HM, FM: NASA 80NSSC17K0716. CR, HS: NASA 80NSSC17K0700. AS, PB: NASA 80NSSC18K1431. DS, AM, KS NASA 80NSSC17K0654. BVM: NSF 1756254. XZ, DG, LG, YH: NASA 80NSSC17K0656 and 80NSSC20K0350.
    Keywords: Biological pump ; NASA field campaign ; NPP fates ; Carbon cycle ; Organic carbon export ; Export pathways
    Repository Name: Woods Hole Open Access Server
    Type: Article
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