Evidence map›Paper›PMID 35933515›Full record

ArticleScientific data2022

A global dataset of seaweed net primary productivity.

Albert Pessarrodona, Karen Filbee-Dexter, Kira A Krumhansl, Morten F Pedersen, Pippa J Moore, Thomas Wernberg

Open access · goldAbstract readDataset
In one paragraph

Article in Scientific data, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed, 2 pooled it
6.1field-weighted citation impact, top 3% of its field
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

15 citing papers in PubMed, 2 syntheses or guidelines pooled it, 60 citations in OpenAlex.

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  13. Global seaweed productivity.Science advances · 2022
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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

6 authors at 4 institutions in 5 countries.

Albert PessarrodonaUWA Oceans Institute and School of Biological Sciences, University of Western Australia, Crawley, Western Australia, 6009, Australia. pessa3@gmail.com.ORCID 0000-0002-6057-9937
Karen Filbee-DexterUWA Oceans Institute and School of Biological Sciences, University of Western Australia, Crawley, Western Australia, 6009, Australia.
Kira A KrumhanslFisheries and Oceans Canada, Bedford Institute of Oceanography, Dartmouth, Nova Scotia, Canada.
Morten F PedersenDepartment of Science and Environment, Roskilde University, Universitetsvej 1, DK-4000, Roskilde, Denmark.
Pippa J MooreSchool of Natural and Environmental Sciences, Newcastle University, Newcastle-Upon-Tyne, NE1 7RU, UK.
Thomas WernbergUWA Oceans Institute and School of Biological Sciences, University of Western Australia, Crawley, Western Australia, 6009, Australia.ORCID 0000-0003-1185-9745
Roskilde University · DKThe University of Western Australia · AUFisheries and Oceans Canada · CANewcastle University · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Net primary productivity (NPP) plays a pivotal role in the global carbon balance but estimating the NPP of underwater habitats remains a challenging task. Seaweeds (marine macroalgae) form the largest and most productive underwater vegetated habitat on Earth. Yet, little is known about the distribution of their NPP at large spatial scales, despite more than 70 years of local-scale studies being scattered throughout the literature. We present a global dataset containing NPP records for 246 seaweed taxa at 429 individual sites distributed on all continents from the intertidal to 55 m depth. All records are standardized to annual aerial carbon production (g C m

Indexed as

EcosystemSeaweedCarbonCarbon CycleEnvironmentCarbon

Identifiers

PMID35933515
PMCPMC9357081
OpenAlexW4290065549

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.