Evidence map›Paper›PMID 42109847›Full record

ArticleiScience2026

Tracing pesticides through terrestrial food webs with wildlife at risk.

Shaorong Chen, Zijian Li

Abstract read
In one paragraph

Article in iScience, 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

2 authors.

Shaorong ChenSchool of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, Guangdong 518107, China.
Zijian LiSchool of Public Health (Shenzhen), Shenzhen Campus of Sun Yat-sen University, Sun Yat-sen University, Shenzhen, Guangdong 518107, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Pesticides support food production but can pose ecological risks through trophic transfer in terrestrial ecosystems. Current approaches integrating contamination evidence across trophic levels with toxicokinetic and spatial models remain limited for wildlife. Here, we present an integrative framework linking empirical contamination data, physiologically based pharmacokinetic modeling, and spatial risk mapping to evaluate pesticide transfer across terrestrial food webs. Using published data from 100 studies across 30 countries, we calculated relative contamination scores for soils, plants, and wildlife and reconstructed average daily doses for representative herbivores, omnivores, and carnivores. Hazard quotients and ecological carcinogenic risks were estimated using international toxicological benchmarks. Results show pronounced spatial heterogeneity and evidence of trophic magnification for several persistent organic pollutants, with higher modeled risks in carnivores than herbivores under comparable environmental burdens. Geographic coverage remains uneven, limiting global inference. The framework is scalable but broader empirical data and independent validation are needed for robust generalizations.

Indexed as

Ecological biochemistryEcologyEnvironmental scienceEnvironmental toxicologyPollutionWildlife toxicology

Identifiers

PMID42109847
PMCPMC13156712

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.