Evidence map›Paper›PMID 42622355›Full record

ArticleGlobal change biology2026

Litter Mixing Effects Modulate UV-Induced Photodegradation Across Grasslands.

Sen Yang, Jiao Su, Pengfei Chang, Yuntao Wu, Jing Wang, Meifeng Deng, Junsheng Huang, Lingli Liu

Abstract read
In one paragraph

Article in Global change biology, 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

8 authors.

Sen YangState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0002-5452-944X
Jiao SuState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0001-5877-1084
Pengfei ChangState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0003-4084-0541
Yuntao WuState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
Jing WangCollege of Life Sciences, Hebei University, Baoding, China.
Meifeng DengState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
Junsheng HuangState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.
Lingli LiuState Key Laboratory of Forage Breeding-by-Design and Utilization, Key Laboratory of Vegetation and Environmental Change, Institute of Botany, Chinese Academy of Sciences, Beijing, China.ORCID 0000-0002-5696-3151

Funding

National Natural Science Foundation of China 32125025National Natural Science Foundation of China 32301347National Natural Science Foundation of China 32330066National Natural Science Foundation of China 32371630
6 · The paper itself

Abstract

UV radiation can strongly affect litter decomposition across broad climatic gradients, but the magnitude of its contribution differs among ecosystems. Current understanding of this process remains largely based on single-species litter experiments, which overlook the compositional complexity of natural litter inputs and the potential role of litter mixing in modulating UV-driven photodegradation. To address this gap, we conducted a mixed-litter decomposition experiment within a UV-manipulation network across a 25° latitudinal gradient spanning four grassland types in China. Using biomass-weighted mixtures of locally dominant species to represent natural litter inputs at each experimental site, we examined how variations in litter diversity and trait dispersion shaped the regional pattern of UV effects on mixed-litter decomposition. After four-year field decomposition, UV attenuation prolonged litter mean residence time by 3%-35% across sites. Litter mixtures with higher taxonomic and phylogenetic diversity showed faster early-stage mass loss, a pattern explained by greater availability of dissolved organic carbon for microbial decomposition. In contrast, greater dispersion in species-level C/N ratios within the litter mixtures imposed increasingly stronger stoichiometric constraint on biotic degradation as decomposition progressed. The magnitude of UV-induced photodegradation increased with UV intensity. However, faster decomposition in phylogenetically diverse mixtures shortened the duration of radiation exposure, thereby constraining the strength of UV-induced litter photodegradation. This mixing-effect-mediated constraint presented a stronger influence than UV exposure intensity on explaining regional variation in UV effects on litter decomposition. Overall, these findings underscore a previously underappreciated role of local litter mixture complexity in modulating the spatial pattern of UV-induced photodegradation across grassland ecosystems. By linking litter mixing effects with UV-driven decomposition, this study extends photodegradation research beyond the common focus on single-species litter and highlights the importance of community-level litter complexity for predicting grassland carbon turnover concurrent with climate change and biodiversity loss.

Indexed as

GrasslandPhotolysisPlant LeavesUltraviolet RaysChinafunctional dispersiongrasslandlitter mixing effectmixed‐litter decompositionphotodegradationspecies diversityultraviolet radiation

Identifiers

PMID42622355
PMCPMC13492095

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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.