Evidence map›Paper›PMID 38092782›Full record

ArticleScientific data2023

An integrated individual-level trait-based phytoplankton dataset from transitional waters.

Maira Laraib, Jessica Titocci, Ilaria Rosati, Alberto Basset

Abstract readDataset
In one paragraph

Article in Scientific data, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

4 authors.

Maira LaraibUniversity of Salento, Department of Biological and Environmental Sciences and Technologies (DiSTeBA), Lecce, Italy. maira.laraib@unisalento.it.ORCID 0000-0002-9704-8072
Jessica TitocciItalian National Research Council (CNR), Institute for Research on Terrestrial Ecosystems (IRET), Lecce, Italy. jessica.titocci@cnr.it.ORCID 0000-0001-9157-1578
Ilaria RosatiItalian National Research Council (CNR), Institute for Research on Terrestrial Ecosystems (IRET), Lecce, Italy.
Alberto BassetUniversity of Salento, Department of Biological and Environmental Sciences and Technologies (DiSTeBA), Lecce, Italy.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Functional trait-based approaches have undergone an extraordinary expansion in phytoplankton ecology. Morpho-functional traits have been shown to vary both within and between populations and species, potentially affecting individual fitness and the network of inter-individual relationships. Here we integrate six fully harmonized phytoplankton morpho-functional trait datasets, characterized by a fine data grain, reporting individual-level data over a large biogeographical area. Datasets refer to transitional water ecosystems, from five biogeographical areas: Northern Atlantic Ocean (Scotland), South-Western Atlantic Ocean (Brazil), South-Western Pacific Ocean (Australia), Indo Pacific Ocean (Maldives) and Mediterranean Sea (Greece and Turkey). The integrated dataset includes 127311 individual phytoplankton records with sampling locations, taxonomic and morphometric information according to Darwin Core standards and semantic annotations. The six FAIR datasets are openly available in the LifeWatch Italy data portal. The datasets have already been used for morpho-functional analyses and hypothesis testing on phytoplankton guilds at different levels of data aggregation and scale, from local to global.

Indexed as

EcosystemPhytoplanktonAtlantic OceanPacific OceanWaterWater

Identifiers

PMID38092782
PMCPMC10719296

What OpenQuestion holds

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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.