Marine snow morphology drives sinking and attenuation in the ocean interior

Abstract. Simultaneous measurements of marine snow (particles larger than 600 µm) morphologies, estimates of their in situ sinking speeds, and midwater attenuation in export plumes were performed for the first time using a biogeochemical (BGC)-Argo float equipped with optical and imaging sensors. The float was deployed and recovered after drifting for 1 year in the sluggish-flow regime of the Angola Basin. Six consecutive chlorophyll a and particulate matter accumulation events were recorded at the surface, each followed by an export plume of sinking aggregates. Objects larger than 600 µm were classified using machine learning recognition and clustered into four morphological categories of marine aggregates. Plankton images were validated by an expert in a few broad categories. Results show that different types of aggregates were produced and exported from the different blooms. The different morphological categories of marine snow had different sinking speeds and attenuation for a similar size, indicating the effect of morphology on sinking speed. However, a typical size-to-sinking relationship for two of the categories and over the larger observed size range (100 µm to a few millimeters) was also observed, indicating the importance of size for sinking. Surprisingly, in situ-calculated sinking speeds were constantly in the lower range of known values usually assessed ex situ, suggesting a methodological effect, which is discussed. Moving away from purely size-based velocity relationships and incorporating these additional morphological aggregate properties will help to improve the mechanistic understanding of particle sinking and provide more accurate flux estimates. When used from autonomous platforms at high frequency, they will also provide increased spatio-temporal resolution for the observation of intermittent export events naturally occurring or induced by human activities.

Authors

Institutions

Publication Details

Journal
Biogeosciences
Published
2025-07-18
DOI
https://doi.org/10.5194/bg-22-3485-2025
Citations
2
Primary Topic
Oceanographic and Atmospheric Processes
Type
article
Field-Weighted Citation Impact
3.59
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Marine snow morphology drives sinking and attenuation in the ocean interior

Lars Stemmann, Miriam Beck, Yawouvi Dodji Soviadan, Alberto Baudena et al.
2 citations
Biogeosciences
Oceanographic and Atmospheric Processes
3.59
article

Marine snow morphology drives sinking and attenuation in the ocean interior

Lars Stemmann, Miriam Beck, Yawouvi Dodji Soviadan, Alberto Baudena, Peter Brandt, Joelle Habib, Rémi Laxenaire, Rainer Kiko, Sabrina Speich, Laetitia Drago, Alexandre Accardo
article en
2 citations

Abstract

Abstract. Simultaneous measurements of marine snow (particles larger than 600 µm) morphologies, estimates of their in situ sinking speeds, and midwater attenuation in export plumes were performed for the first time using a biogeochemical (BGC)-Argo float equipped with optical and imaging sensors. The float was deployed and recovered after drifting for 1 year in the sluggish-flow regime of the Angola Basin. Six consecutive chlorophyll a and particulate matter accumulation events were recorded at the surface, each followed by an export plume of sinking aggregates. Objects larger than 600 µm were classified using machine learning recognition and clustered into four morphological categories of marine aggregates. Plankton images were validated by an expert in a few broad categories. Results show that different types of aggregates were produced and exported from the different blooms. The different morphological categories of marine snow had different sinking speeds and attenuation for a similar size, indicating the effect of morphology on sinking speed. However, a typical size-to-sinking relationship for two of the categories and over the larger observed size range (100 µm to a few millimeters) was also observed, indicating the importance of size for sinking. Surprisingly, in situ-calculated sinking speeds were constantly in the lower range of known values usually assessed ex situ, suggesting a methodological effect, which is discussed. Moving away from purely size-based velocity relationships and incorporating these additional morphological aggregate properties will help to improve the mechanistic understanding of particle sinking and provide more accurate flux estimates. When used from autonomous platforms at high frequency, they will also provide increased spatio-temporal resolution for the observation of intermittent export events naturally occurring or induced by human activities.

BiogeosciencesVol. 22(14)
Florida State University (US), Centre National de la Recherche Scientifique (FR), Ifremer (FR), Institut Universitaire de France (FR), Université de Montpellier (FR), École Normale Supérieure - PSL (FR), Christian-Albrechts-Universität zu Kiel (DE), GEOMAR Helmholtz Centre for Ocean Research Kiel (DE), Sorbonne Université (FR), Laboratoire de Météorologie Dynamique (FR), Météo-France (FR), Istituto di Scienze Marine del Consiglio Nazionale delle Ricerche (IT), Institute of Structure of Matter (IT), Laboratoire de l'Atmosphère et des Cyclones (RE), Marine Biodiversity Exploitation and Conservation (FR), Fondation Pour la Recherche Sur la Biodiversité (FR), Laboratoire d'Océanographie et du Climat : Expérimentations et Approches Numériques (FR), Laboratoire d’Océanographie de Villefranche (FR), Institut de Recherche pour le Développement (FR), University of Lomé (TG)
Openalex Percentile: Top 7%
Oceanographic and Atmospheric Processes
3.59
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.