Specialist Generalist Trade Offs in Microbial Growth Rates Across Soil Habitats

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Specialist Generalist Trade Offs in Microbial Growth Rates Across Soil Habitats

Authors

Foley, M.; Sokol, N.; Stone, B.; Blazewicz, S. J.; Estera-Molina, K.; Greenlon, A.; Hayer, M.; Kimbrel, J.; Pett-Ridge, J.; Hungate, B. A.

Abstract

Microbial ecological strategies are shaped by a fundamental trade-off: is it better to specialize and thrive in a narrow niche or generalize and persist across diverse environments? In soils, this trade off is particularly relevant in the rhizosphere and detritusphere, where microorganisms encounter distinct resource inputs from living and decaying roots. Using H218O quantitative stable isotope probing (qSIP), we measured in situ bacterial and fungal growth rates in the rhizosphere, the root detritusphere, and in the combined presence of rhizosphere + root detritus to test whether specialists (microbes growing in a single habitat) grow faster than generalists that persist across multiple environments. Specialists grew consistently faster than generalists, suggesting a trade off between the breadth of environmental conditions a microorganism can tolerate and its ability to grow quickly in a specific habitat. This cost to broad niche adaptation was apparent for bacteria, but growth rates of fungal saprotrophs varied little between specialists and generalists, reflecting how fundamental differences in life history strategies between bacteria and fungi can shape microbial responses to resource availability and habitat heterogeneity. Net relatedness and nearest taxon indices indicated total bacterial communities were phylogenetically clustered while specialist and generalist communities were phylogenetically random, suggesting that functional traits, not lineage, best predict ecological strategy. In annual grassland soils, fast growing specialists may dominate ecosystem processes when resources abound, and slow growing generalists may sustain element transformations when conditions shift; understanding this interplay is key to predicting soil-carbon trajectories.

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