Dataset: Global reconstructions of particle biovolume, size distribution, and carbon export flux from the seasonal euphotic zone and maximum winter time mixed layer from particle profiles conducted during cruises from 2008 to 2020

Final no updates expectedDOI: 10.26008/1912/bco-dmo.856942.2Version 2 (2023-02-02)Dataset Type:Other Field ResultsDataset Type:model results

Principal Investigator: Daniele Bianchi (University of California-Los Angeles)

Co-Principal Investigator: Daniel Clements (University of California-Los Angeles)

BCO-DMO Data Manager: Amber D. York (Woods Hole Oceanographic Institution)


Project: Collaborative Research: Understanding the distribution and biogeochemical role of anaerobic microenvironments in the ocean (Ocean Particles and Microenvironments)


Abstract

Global reconstructions of particle biovolume, size distribution, and carbon export flux from the seasonal euphotic zone and maximum winter time mixed layer.

Methodology:

This work is based on the compilation of over 6800 profiles of particulate matter observations from Underwater Vision Profilers (UVP5) (Rainer, 2021). The biovolume of the particle size distribution is calculated as the equivalent spherical volume of the particle size distribution  (PSD), by summing the product of particle counts time particle volume in each size class. The slope of the PSD is calculated assuming a power law distribution for the particle abundance, by linear least square fit of the log of particle counts vs. the log of particle size. These quantities are estimated from two different depth horizons, the mixed layer depth (MLD_Export.nc) and the euphotic zone depth (Euphotic_Export.nc). To convert sparse observations to a global climatology, we trained 100 ensembles of regressions trees (Random Forests, RF) to predict biovolume and slope based on their relationship to well-sampled physical and biogeochemical predictors.

We calculate the particle sinking speed and carbon content by combining PSD reconstruction (biovolume and slope) with an empirical relationship between particle size, carbon content and sinking speed, the parameters of which are optimized to match in situ particle flux observations (Bisson et al. 2018). The flux values are calculated as the sum of the PSD time the sinking carbon parameters, for each grid cell. The error for reconstructed quantities is given by the standard deviation of 100 independent realizations of the RF reconstructions.

Sampling and analytical procedures: 

This dataset contains a compilation of data from multiple sources.  A list of all datasets and the associated information, including cruise name, is included.

Observations of Particle size and biovolume are made via the UVP5 camera, which is lowered in the water column on a CTD rosette. Images are captured at up to 30 images per second while the instrument is lowered at 1m/s. Images are analyzed and the pixel size of each particle is translated into a particle size, and the abundance calculated, following the method described by Picheral et al. (2010). 


The data is compiled from multiple sources published and unpublished, and was accessed from EcoPart, the particle module of EcoTaxa https://ecotaxa.obs-vlfr.fr/part/ (Picheral et al., 2017).

Instruments

Observations of particle abundance and biovolume were made with the Underwater Vision Profiler, version 5 (UVP5).


Related Datasets

IsRelatedTo

Dataset: Global depth resolved reconstruction of particle size distribution and carbon export
Relationship Description: Dataset related to the same cruise list.
Clements, D., Bianchi, D. (2024) Global reconstructions of particle biovolume, size distribution, and carbon export flux validated for the upper 2000m of the water column from particle profiles conducted during cruises from 2008 to 2020. Biological and Chemical Oceanography Data Management Office (BCO-DMO). (Version 1) Version Date 2024-10-03 http://lod.bco-dmo.org/id/dataset/939274

Related Publications

Results

Clements, D. J., Yang, S., Weber, T., Mcdonnell, A., Kiko, R., Stemmann, L., & Bianchi, D. (2021). Constraining the ocean’s biological pump with in situ 1 optical observations and supervised learning. Part 2: 2 Carbon Flux. https://doi.org/10.1002/essoar.10509084.1
IsDerivedFrom

Kiko, Rainer (2021): The global marine particle size distribution dataset obtained with the Underwater Vision Profiler 5 - version 1. PANGAEA, https://doi.pangaea.de/10.1594/PANGAEA.924375
IsDerivedFrom

Picheral M, Colin S, Irisson J-O (2017). EcoTaxa, a tool for the taxonomic classification of images. http://ecotaxa.obs-vlfr.fr
Methods

Bisson, K. M., Siegel, D. A., DeVries, T., Cael, B. B., & Buesseler, K. O. (2018). How Data Set Characteristics Influence Ocean Carbon Export Models. Global Biogeochemical Cycles, 32(9), 1312–1328. doi:10.1029/2018gb005934
Methods

Picheral, M., Guidi, L., Stemmann, L., Karl, D. M., Iddaoud, G., & Gorsky, G. (2010). The Underwater Vision Profiler 5: An advanced instrument for high spatial resolution studies of particle size spectra and zooplankton. Limnology and Oceanography: Methods, 8(9), 462–473. doi:10.4319/lom.2010.8.462