Evidence map›Paper›PMID 35495707›Full record

ArticleFrontiers in microbiology2022

Imaging Technologies Build Capacity and Accessibility in Phytoplankton Species Identification Expertise for Research and Monitoring: Lessons Learned During the COVID-19 Pandemic.

Sophie Clayton, Leah Gibala-Smith, Kathryn Mogatas, Chanel Flores-Vargas, Kayla Marciniak, Maci Wigginton, Margaret R Mulholland

Abstract read
In one paragraph

Article in Frontiers in microbiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Sophie ClaytonDepartment of Ocean and Earth Sciences, Old Dominion University, Norfolk, VA, United States.
Leah Gibala-SmithDepartment of Ocean and Earth Sciences, Old Dominion University, Norfolk, VA, United States.
Kathryn MogatasDepartment of Ocean and Earth Sciences, Old Dominion University, Norfolk, VA, United States.
Chanel Flores-VargasDepartment of Ocean and Earth Sciences, Old Dominion University, Norfolk, VA, United States.
Kayla MarciniakDepartment of Biology, Old Dominion University, Norfolk, VA, United States.
Maci WiggintonDepartment of Ocean and Earth Sciences, Old Dominion University, Norfolk, VA, United States.
Margaret R MulhollandDepartment of Ocean and Earth Sciences, Old Dominion University, Norfolk, VA, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

As primary producers, phytoplankton play an integral role in global biogeochemical cycles through their production of oxygen and fixation of carbon. They also provide significant ecosystem services, by supporting secondary production and fisheries. Phytoplankton biomass and diversity have been identified by the Global Ocean Observing System (GOOS) as Essential Ocean Variables (EOVs), properties that need to be monitored to better understand and predict the ocean system. Phytoplankton identification and enumeration relies on the skills and expertise of highly trained taxonomic analysts. The training of new taxonomic analysts is intensive and requires months to years of supervised training before an analyst is able to independently and consistently apply identification skills to a sample. During the COVID-19 pandemic, access to laboratories was greatly restricted and social distancing requirements prevented supervised training. However, access to phytoplankton imaging technologies such as the Imaging FlowCytobot (IFCB), FlowCam, and PlanktoScope, combined with open online taxonomic identification platforms such as EcoTaxa, provided a means to continue monitoring, research, and training activities remotely when in-person activities were restricted. Although such technologies can not entirely replace microscopy, they have a great potential for supporting an expansion in taxonomic training, monitoring, surveillance, and research capacity. In this paper we highlight a set of imaging and collaboration tools and describe how they were leveraged during laboratory lockdowns to advance research and monitoring goals. Anecdotally, we found that the use of imaging tools accelerated the training of new taxonomic analysts in our phytoplankton analysis laboratory. Based on these experiences, we outline how these technologies can be used to increase capacity in taxonomic training and expertise, as well as how they can be used more broadly to expand research opportunities and capacity.

Indexed as

environmental monitoringharmful algal bloom (HAB)imaging cytometryphytoplanktonphytoplankton ecologyplanktonspecies identificationtaxonomic expertise

Identifiers

PMID35495707
PMCPMC9048821

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.