2023
DOI: 10.1101/2023.11.20.567900
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Microeukaryote metabolism across the western North Atlantic Ocean revealed through autonomous underwater profiling

Natalie R. Cohen,
Arianna I. Krinos,
Riss M. Kell
et al.

Abstract: Protists (microeukaryotes) are key contributors to marine carbon cycling, influencing the transfer of energy to higher trophic levels and the vertical movement of carbon to the ocean interior. Their physiology, ecology, and interactions with the chemical environment are still poorly understood in offshore ecosystems, and especially in the deep ocean. Using the Autonomous Underwater Vehicle (AUV)Clio, the microbial community along a 1,050 km transect in the western North Atlantic Ocean was surveyed at 10-200 m … Show more

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Cited by 4 publications
(3 citation statements)
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“…Samples for the informatic component were collected by the autonomous underwater vehicle Clio. The vehicle and its sampling characteristics were used as previously described (Breier et al, 2020;Cohen et al, 2023). Specifically, samples Ocean-8 and Ocean-11 were also collected from the BATS station on R/V Atlantic Explorer expedition identifier AE1913 (also described as BATS validation track BV55 32.75834 o N 65.7374 o W).…”
Section: Sample Collection and Metadatamentioning
confidence: 99%
“…Samples for the informatic component were collected by the autonomous underwater vehicle Clio. The vehicle and its sampling characteristics were used as previously described (Breier et al, 2020;Cohen et al, 2023). Specifically, samples Ocean-8 and Ocean-11 were also collected from the BATS station on R/V Atlantic Explorer expedition identifier AE1913 (also described as BATS validation track BV55 32.75834 o N 65.7374 o W).…”
Section: Sample Collection and Metadatamentioning
confidence: 99%
“…𝑚 −2 respectively. All UVP data processing was done using the EcotaxaTools package in R (Barth 2023).…”
Section: Rhizaria Imaging Processing and Quantificationmentioning
confidence: 99%
“…DNA metabarcoding studies have revealed insights into the distributional patterns (Biard et al, 2017; Blanco-Bercial et al, 2022; Decelle et al, 2013; Llopis Monferrer et al, 2022; Mars Brisbin et al, 2020; Sogawa et al, 2022), ecological relationships (Decelle et al, 2012; Nakamura et al, 2023), and contribution to biogeochemical fluxes (Guidi et al, 2016; Gutierrez-Rodriguez et al, 2019). Transcriptomic and proteomic approaches also have been used to quantify Rhizaria contribution to community metabolism (Cohen et al, 2023). Yet, despite the excellent taxonomic resolution provided by molecular approaches, they do not provide a truly quantitative metric for estimating Rhizaria abundance or biomass.…”
Section: Introductionmentioning
confidence: 99%