Evidence map›Paper›PMID 42683243›Full record

ArticleEcology and evolution2026

Impact of Rainfall on Aquatic and Terrestrial Species Monitoring Using Riverine Environmental DNA.

Chen Xu, Kei Nukazawa

Abstract read
In one paragraph

Article in Ecology and evolution, 2026. 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

2 authors.

Chen XuInterdisciplinary Graduate School of Agriculture and Engineering University of Miyazaki Miyazaki Japan.ORCID https://orcid.org/0009-0004-2487-1625
Kei NukazawaDepartment of Civil and Environmental Engineering, Faculty of Engineering University of Miyazaki Miyazaki Japan.ORCID https://orcid.org/0000-0001-5356-2064

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Water-based environmental DNA (eDNA) can simultaneously detect aquatic and terrestrial species during watershed-scale eDNA biodiversity monitoring. However, detecting terrestrial species remains a challenge because of their complex environmental effects. This study targeted vertebrate eDNA transported from land to rivers through surface runoff during rainfalls in three rivers within the Kiyotake River watershed, Japan. We compared the relative detection indices of different taxonomic groups under rainfall and non-rainfall conditions and determined how environmental factors (e.g., discharge and filtration volume) influence sample-level alpha and beta diversity. The results showed that mammals and amphibians were detected more frequently after rainfall, whereas fish showed lower detection frequencies due to reduced filtration volumes caused by filter clogging. Generalized linear mixed model analyses revealed that river discharge had significant negative effects on the detection number, whereas filtration volume had a significant positive effect. Furthermore, Permutational Multivariate ANOVA indicated that filtration volume and rainfall occurrence significantly affected beta diversity. Our findings highlight the importance of filtration volume for detecting alpha and beta diversity and demonstrate that eDNA-based biomonitoring remains effective during rainfall events, offering practical guidance for enhancing biodiversity assessments at the watershed scale. Such approaches may provide an efficient tool for detecting not only aquatic species, but also terrestrial vertebrates that are otherwise difficult to survey using conventional field methods.

Indexed as

environmental DNA metabarcodinggeneralized linear mixed modelPermutational Multivariate Analysis of Variancerainfallvertebrate

Identifiers

PMID42683243
PMCPMC13531241

What OpenQuestion holds

Textmetadata
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.