Evidence map›Paper›PMID 41708634›Full record

ArticleScientific data2026

A Global Dataset on Nutrient Removal Capacity by Marine Macroalgae.

Peiling Xie, Weidong Feng, Junyu He, Ziwan Wang, Jiaping Wu, Yuanyuan Lu, Xiangtian Yang, Jiahao Dong, Xinqiang Liang

Abstract readDataset
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific data, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

9 authors.

Peiling Xie *Key Laboratory of Water Pollution Control and Environmental Security Technology, Zhejiang Province, College of Environmental Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Weidong Feng *Key Laboratory of Water Pollution Control and Environmental Security Technology, Zhejiang Province, College of Environmental Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Junyu HeState Key Laboratory of Ocean Sensing & Ocean College, Zhejiang University, Zhoushan, 316021, China.
Ziwan WangKey Laboratory for Environment and Disaster Monitoring and Evaluation of Hubei, Jianghan Plain-Honghu Lake Station for Wetland Ecosystem Research, Innovation Academy for Precision Measurement Science and Technology, Chinese Academy of Sciences, Wuhan, China.
Jiaping WuState Key Laboratory of Ocean Sensing & Ocean College, Zhejiang University, Zhoushan, 316021, China.
Yuanyuan LuKey Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang, 310032, China.
Xiangtian YangKey Laboratory of Water Pollution Control and Environmental Security Technology, Zhejiang Province, College of Environmental Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Jiahao DongKey Laboratory of Water Pollution Control and Environmental Security Technology, Zhejiang Province, College of Environmental Resource Sciences, Zhejiang University, Hangzhou, 310058, China.
Xinqiang LiangKey Laboratory of Water Pollution Control and Environmental Security Technology, Zhejiang Province, College of Environmental Resource Sciences, Zhejiang University, Hangzhou, 310058, China. liang410@zju.edu.cn.ORCID http://orcid.org/0000-0002-3521-9761

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Eutrophication driven by excessive nutrient inputs poses a growing threat to marine ecosystems worldwide. Macroalgal aquaculture has been recognized as a promising nature-based solution to mitigate nutrient enrichment; however, a systematic global synthesis of nutrient removal capacity across macroalgae species under varying environmental conditions remains lacking. Here, this study presents the first comprehensive open-access global dataset on nutrient removal capacity by marine macroalgae. The dataset comprises 2,011 records from 149 theses or peer-reviewed articles published between 1995 and 2024, covering 113 macroalgae species from 234 sampling sites across 23 countries on six continents. Each record includes publication details, geographic and taxonomic information, environmental parameters, and macroalgal nutrient removal performance (removal rates, efficiencies, and amounts). The dataset is organized into multiple Date tables, including subsets for nutrient-specific removal metrics and in situ experiments, thereby enabling tailored analyses. This resource provides the most extensive synthesis to date of macroalgal nutrient uptake capacity, and supports evidence-based functional macroalgal aquaculture planning, targeted eutrophication management, and marine ecosystem restoration.

Indexed as

EutrophicationNutrientsSeaweedAquacultureEcosystem

Identifiers

PMID41708634
PMCPMC13031918

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.