Evidence map›Paper›PMID 41249355›Full record

ArticleScientific reports2025

Vegetation change threatens the sustainability of cultural keystone species and traditional ecological knowledge in a social-ecological system.

Shiori Takahashi, Jun Nishihiro

Abstract read
In one paragraph

Article in Scientific reports, 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

2 authors.

Shiori TakahashiGraduate School of Agricultural and Life Science, The University of Tokyo, 1-1-1, Yayoi, Bunkyo-ku, Tokyo, 113-8657, Japan. shiori-t372@g.ecc.u-tokyo.ac.jp.
Jun NishihiroCenter for Climate Change Adaptation, National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki, 305-0053, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Traditional ecological knowledge (TEK) and cultural practices are often closely linked to local biodiversity through keystone species. However, the long-term ecological dynamics affecting the utility of such species remain underexplored. This study combines TEK with 40 years of vegetation monitoring in a Japanese wetland to examine how ecological change affects culturally important thatch. Interviews and sample observations categorized species into four ranks, from essential to undesirable for thatching. This index was then applied to analyze long-term vegetation monitoring data. Conventional indices such as species richness and the Shannon-Weaver index showed no clear trends, while NMDS detected shifts in species composition. However, these shifts were not directly linked to cultural usefulness. In contrast, the usefulness-based assessment revealed a substantial decline in species essential for high-quality thatch and an increase in undesirable species. This shift suggests a decline in thatch quality and a potential threat to the sustainability of the social-ecological system reliant on thatch use. Our findings demonstrate the value of integrating TEK with ecological monitoring to detect ecologically and culturally significant change. This interdisciplinary approach yields insights into social-ecological interactions that would be missed by standard metrics, and can inform context-sensitive management strategies to support system resilience.

Indexed as

Conservation of Natural ResourcesKnowledgeBiodiversityCultureEcologyEcosystemHumansJapanWetlandsBiocultural diversityCultural keystone speciesLocal ecological knowledgeMarsh vegetationSocial-ecological systemsVegetation monitoring

Identifiers

PMID41249355
PMCPMC12623805

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Registered trials

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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.