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bioRxiv ; 2024 Jun 26.
Artigo em Inglês | MEDLINE | ID: mdl-38979227

RESUMO

Microbial communities living on plant leaves can positively or negatively influence plant health and, by extension, can impact whole ecosystems. Most research into the leaf microbiome consists of snapshots, and little is known about how microbial communities change over time. Weather and host physiological characteristics change over time and are often collinear with other time-varying factors, such as substrate availability, making it difficult to separate the factors driving microbial community change. We leveraged repeated measures over the course of an entire year to isolate the relative importance of environmental, host physiological, and substrate age-related factors on the assembly, structure, and composition of leaf-associated fungal communities. We applied both culturing and sequencing approaches to investigate these communities, focusing on a foundational, widely-distributed plant of conservation concern: basin big sagebrush ( Artemisia tridentata subsp. tridentata ). We found that changes in alpha diversity were independently affected by the age of a community and the air temperature. Surprisingly, total fungal abundance and species richness were not positively correlated and responded differently, sometimes oppositely, to weather. With regard to beta diversity, communities were more similar to each other across similar leaf ages, air temperatures, leaf types, and δ 13 C stable isotope ratios. Nine different genera were differentially abundant with air temperature, δ 13 C, leaf type, and leaf age, and a set of 20 genera were continuously present across the year. Our findings highlight the necessity for longer-term, repeated sampling to parse drivers of temporal change in leaf microbial communities. Open Research Statement: All ITS DNA amplicon sequence raw data are deposited in the NCBI Sequence Read Archive (SRA), BioProject number PRJNA1107252, data will be released upon publication. All community data, metadata, taxonomic data, and R code necessary to reproduce these results are deposited in the GitHub repository archived on Zenodo: 10.5281/zenodo.11106439.

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