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Decomposition responses to climate depend on microbial community composition

Significance We overcame the difficulty of disentangling biotic and abiotic effects on decomposition by using the largest field-based reciprocal transplant experiment to date. We showed that decomposition responses to climate depend on the composition of microbial communities, which is not considered in terrestrial carbon models. Microbial communities varied in their effects on both mass loss and types of carbon decomposed in an interactive manner not predicted by current theory. Contrary to the traditional paradigm, bacterial communities appeared to have a stronger impact on grassland litter decomposition rates than fungi. Furthermore, bacterial communities shifted more rapidly in response to changing climates than fungi. This information is critical to improving global terrestrial carbon models and predicting ecosystem responses to climate change.
- University of California System United States
- University of California, Riverside United States
- University of Denver United States
- University of California, Riverside United States
- University of California, Irvine United States
leaf litter decomposition, 550, Bacteria, Altitude, Climate Change, Microbiota, Fungi, reciprocal transplant, California, Carbon Cycle, Climate Action, Plant Leaves, elevation gradient, fungi, Infection, bacteria, Ecosystem
leaf litter decomposition, 550, Bacteria, Altitude, Climate Change, Microbiota, Fungi, reciprocal transplant, California, Carbon Cycle, Climate Action, Plant Leaves, elevation gradient, fungi, Infection, bacteria, Ecosystem
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).262 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 0.1% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 0.1%
