Evidence map›Paper›PMID 41185758›Full record

ArticleEcology and evolution2025

Trophic Relationships of Aquatic Species Offer Valuable Insights Into Shallow Lake Ecosystem Recovery.

Yajun Qiao, Min Pang, Mengyu Lv, Tianzhe Zhu, Wennuo Han, Zhao Li, Xiaolong Lin, Peidong Su, Pei Qu, Chunhui Zhang

Abstract read
In one paragraph

Article in Ecology and evolution, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

10 authors.

Yajun QiaoSchool of Chemical & Environmental Engineering China University of Mining & Technology Beijing China.
Min PangMarine Ecology Research Center, First Institute of Oceanography Ministry of Natural Resources of the People's Republic of China Qingdao Shandong Province China.
Mengyu LvEcological and Environmental Monitoring Center of Xiong'an New Area Xiong'an New Area Hebei Province China.
Tianzhe ZhuEcological and Environmental Monitoring Center of Xiong'an New Area Xiong'an New Area Hebei Province China.
Wennuo HanChina National Environmental Monitoring Center Beijing China.
Zhao LiChina National Environmental Monitoring Center Beijing China.
Xiaolong LinCollege of Fisheries and Life Science Shanghai Ocean University Shanghai China.ORCID https://orcid.org/0000-0001-6544-6204
Peidong SuSchool of Chemical & Environmental Engineering China University of Mining & Technology Beijing China.
Pei QuMarine Ecology Research Center, First Institute of Oceanography Ministry of Natural Resources of the People's Republic of China Qingdao Shandong Province China.ORCID https://orcid.org/0000-0001-8179-660X
Chunhui ZhangSchool of Chemical & Environmental Engineering China University of Mining & Technology Beijing China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Shallow freshwater lakes are vital for ecological and climate regulation, but many are degrading. Although restoration efforts are underway to improve water quality, research on their trophic structures is still limited. Baiyangdian Lake (BYD), a typical shallow lake in northern China, has seen improvements in water quality, biodiversity, and aquatic plant biomass after restoration. However, it remains unclear whether its food web's trophic structure has fully recovered. This study collected various field samples from BYD in 2023 and reconstructed BYD's current trophic structure using δ

Indexed as

ecosystem restorationenergy flowshallow freshwater lakestable isotopic analysistrophic structure

Identifiers

PMID41185758
PMCPMC12579968

What Socratic 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 Socratic graph.