ReviewFundamental research2026
The "Ecological Node-Food Web" based ecological risk assessment.
Review in Fundamental research, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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.
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.
Who cites it
1 citing paper in PubMed.
- Advancing the science of systemic environmental risk in an era of global change.Fundamental research · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Traditional aquatic ecological risk assessments are often constrained by a heavy reliance on extensive toxicological data and a limited consideration of interspecies interactions. To address these limitations, this study proposes a novel framework: the "ecological node-food web" method. This approach establishes dose-response relationships between pollutants and ecosystem-level toxicity endpoints by integrating toxicological data from key "ecological node" species with food web modeling. Results demonstrate that data from a few key nodes can effectively mimic ecosystem-wide responses to pollutants. Compared to conventional methods, this approach reduces the need for extensive datasets, enhances cost-effectiveness, and elucidates risk mechanisms through changes in community structure. The method ultimately enables the derivation of scientifically robust ecological risk thresholds.
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What OpenQuestion holds
Registered trials
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.