Revealing the roles of biotic factors in driving community assembly, which is crucial for the understanding of biodiversity and ecosystem functions, is a fundamental but infrequently investigated subject in microbial ecology. Here, combining a cross-biome observational study with an experimental microcosm study, we provided evidence to reveal the major roles of biotic factors (i.e., soil fungi and cross-kingdom species associations) in determining soil bacterial biogeography and community assembly in complex terrestrial ecosystems of the arid regions of northwest China. The results showed that the soil fungal richness mediates the balance of assembly processes of bacterial communities, and stochastic assembly processes decreased with increasing fungal richness. Our results further suggest that the predicted increase in aridity conditions due to climate change will reduce bacterial α-diversity, particularly in desert soils and subsurface layer, and induce more negative species associations. Together, our study represents a significant advance in linking soil fungi to the mechanisms underlying bacterial biogeographic patterns and community assembly in arid ecosystems under climate aridity and land-use change scenarios.
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http://dx.doi.org/10.1002/imt2.2 | DOI Listing |
Ecol Evol
January 2025
Alfred Wegener Institute, Helmholtz Centre for Polar and Marine Research, Polar Terrestrial Environmental Systems Potsdam Germany.
Mountains with complex terrain and steep environmental gradients are biodiversity hotspots such as the eastern Tibetan Plateau (TP). However, it is generally assumed that mountain terrain plays a secondary role in plant species assembly on a millennial time-scale compared to climate change. Here, we investigate plant richness and community changes during the last 18,000 years at two sites: Lake Naleng and Lake Ximen on the eastern TP with similar elevation and climatic conditions but contrasting terrain.
View Article and Find Full Text PDFG3 (Bethesda)
January 2025
Department of Microbiology, University of Tennessee, Knoxville, Knoxville, TN 37916, USA.
Aulacorthum solani is a worldwide agricultural pest aphid capable of feeding on a wide range of host plants. This insect is a vector of plant viruses and causes injury to crops including stunted growth from the loss of phloem. We found that the publicly available genome for A.
View Article and Find Full Text PDFFEMS Microbiol Ecol
January 2025
NIAB East Malling, New Road, Kent, ME19 6BJ, UK.
Severity of European apple canker caused by Neonectria ditissima can vary between locations and apple genotypes. We investigated how location, cold storage/planting season, and apple scion genotype affect root-associated microbial communities. Additionally, we investigated whether differences in abundance of specific taxa could be associated with canker lesion counts.
View Article and Find Full Text PDFEnviron Res
January 2025
College of Hydrology and Water Resources, Hohai University, Nanjing 210098, China.
Estuarine ecosystems have been threatened by increasing anthropogenic and natural pressures, yet the integral understanding of their stability characteristics of microbial communities at taxonomic, habitat, and spatial scales remains limited. In this study, the Mulan River estuary in southeastern China was selected to compare the stability characteristics of bacterial and protistan communities in water and sediments over three hydrological periods, and to explore their spatial variations along the estuarine continuum from river to ocean. The potential driving mechanisms of stability characteristics were also explored.
View Article and Find Full Text PDFCurr Opin Microbiol
January 2025
Department of Plant Biology, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA. Electronic address:
Designing microbiomes for applications in health, bioengineering, and sustainability is intrinsically linked to a fundamental theoretical understanding of the rules governing microbial community assembly. Microbial ecologists have used a range of mathematical models to understand, predict, and control microbiomes, ranging from mechanistic models, putting microbial populations and their interactions as the focus, to purely statistical approaches, searching for patterns in empirical and experimental data. We review the success and limitations of these modeling approaches when designing novel microbiomes, especially when guided by (inevitably) incomplete experimental data.
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