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Constraining the Particle Size Distribution of Large Marine Particles in the Global Ocean With In Situ Optical Observations and Supervised Learning.
Clements, D. J., Yang, S., Weber, T., McDonnell, A. M. P., Kiko, Rainer , Stemmann, L. and Bianchi, D. (2022) Constraining the Particle Size Distribution of Large Marine Particles in the Global Ocean With In Situ Optical Observations and Supervised Learning. Global Biogeochemical Cycles, 36 (5). Art.Nr. e2021GB007276. DOI 10.1029/2021GB007276.
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Abstract
The abundance and size distribution of marine particles control a range of biogeochemical and ecological processes in the ocean, including carbon sequestration. These quantities are the result of complex physical-biological interactions that are difficult to observe, and their spatial and temporal patterns remain uncertain. Here, we present a novel analysis of particle size distributions (PSDs) from a global compilation of in situ Underwater Vision Profiler 5 (UVP5) optical measurements. Using a machine learning algorithm, we extrapolate sparse UVP5 observations to the global ocean from well-sampled oceanographic variables. We reconstruct global maps of PSD parameters (biovolume [BV] and slope) for particles at the base of the euphotic zone. These reconstructions reveal consistent global patterns, with high chlorophyll regions generally characterized by high particle BV and flatter PSD slope, that is, a high relative abundance of large versus small particles. The resulting negative correlations between particle BV and slope further suggests synergistic effects on size-dependent processes such as sinking particle fluxes. Our approach and estimates provide a baseline for an improved understanding of particle cycles in the ocean, and pave the way to global, three-dimensional reconstructions of PSD and sinking particle fluxes from the growing body of UVP5 observations.
Document Type: | Article |
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Keywords: | particle biovolume (BV) |
Refereed: | Yes |
Open Access Journal?: | No |
Publisher: | AGU |
Related URLs: | |
Projects: | CUSCO |
Date Deposited: | 02 Jan 2023 13:08 |
Last Modified: | 07 Feb 2024 15:46 |
URI: | https://oceanrep.geomar.de/id/eprint/57548 |
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