ArticleBMC plant biology2026
Effects of light intensity on the Panax quinquefolius L. growth and soil microbial communities under reduced light spatial heterogeneity: an application to agroforestry systems.
Article in BMC plant 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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors.
Funding
Abstract
The development of under-forest economy within agroforestry systems can enhance the efficiency of land and forest resource utilization, protect the ecological environment, and promote the sustainable development of forests. Forest understory American ginseng (Panax quinquefolius L.) often experiences spatial variability in light availability. However, the impact of light intensity under reduced spatial heterogeneity on soil microenvironments and the regulation of plant physiological traits to promote P. quinquefolius growth remains insufficiently explored. This study adopts field experiments in forest ecosystems to explore how light intensity influences P. quinquefolius physiology, soil biochemical properties, and microbial communities under reduced light spatial heterogeneity. The results indicate that, under reduced spatial heterogeneity with a light transmittance of 13.1%, P. quinquefolius exhibits coordinated physiological responses. The 13.1% light transmittance treatment decreases hydrogen peroxide content, while increasing net photosynthetic rate and chlorophyll content. These changes further improve root dry weight, which is significantly higher than that under 0.7%, 6.4%, and 19.8% light transmittance (with increases of 600.0%, 50.0%, and 5.0%, respectively). Additionally, soil urease activity, pH, and alkali-hydrolyzable nitrogen content are elevated, along with the relative abundance of pH-related microorganisms (e.g., unclassified_Leotiomycetes) and denitrifying bacteria (e.g., unclassified_Gemmatimonadaceae, Anaeromyxobacter, and Bradyrhizobium). The results of the Partial least squares path modeling analysis show that under reduced spatial light heterogeneity in the agroforestry system, light intensity directly promotes the growth of P. quinquefolius by modulating its physiological characteristics. Furthermore, light intensity indirectly fosters the growth of P. quinquefolius by improving soil biological properties (Urease, Sucrase, Catalase, Dehydrogenase, Acid phosphatase) and chemical properties (pH, Alkali-hydrolyzable nitrogen, Available potassium) through the regulation of its physiological characteristics. In conclusion, the optimal light transmittance for P. quinquefolius growth under reduced spatial heterogeneity is 13.1%. These findings offer practical insights for managing P. quinquefolius cultivation in forest ecosystems, contributing to the sustainable development of agroforestry systems.
Indexed as
Identifiers
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.