Summary Root exudates play an important role in ecosystem response to climate change, but the functional consequences of drought‐induced changes in the quality of root exudates are unknown. Here, we addressed this knowledge gap in a unique experimental approach. We subjected two common grassland species that differ widely in their growth strategies and root systems, the grass Holcus lanatus and the forb Rumex acetosa, to 2 wk of drought. We collected root exudates and soils at the end of the drought and after 2 wk of recovery and readded all root exudates to all soils in a fully reciprocal set‐up to measure root‐exudate‐induced respiration. We found that soil treatment was unimportant for determining root‐exudate‐induced respiration. By contrast, root exudates collected from plants that had experienced drought clearly triggered more soil respiration than exudates from undroughted plants. Importantly, this increased respiration compensated for the lower rates of root exudation in droughted plants. Our findings reveal a novel mechanism through which drought can continue to affect ecosystem carbon cycling, and a potential plant strategy to facilitate regrowth through stimulating microbial activity. These findings have important implications for understanding plant and ecosystem response to drought.

The emergence of high-throughput DNA sequencing methods provides unprecedented opportunities to further unravel bacterial biodiversity and its worldwide role from human health to ecosystem functioning. However, despite the abundance of sequencing studies, combining data from multiple individual studies to address macroecological questions of bacterial diversity remains methodically challenging and plagued with biases. Here, using a machine-learning approach that accounts for differences among studies and complex interactions among taxa, we merge 30 independent bacterial data sets comprising 1,998 soil samples from 21 countries. Whereas previous meta-analysis efforts have focused on bacterial diversity measures or abundances of major taxa, we show that disparate amplicon sequence data can be combined at the taxonomy-based level to assess bacterial community structure. We find that rarer taxa are more important for structuring soil communities than abundant taxa, and that these rarer taxa are better predictors of community structure than environmental factors, which are often confounded across studies. We conclude that combining data from independent studies can be used to explore bacterial community dynamics, identify potential 'indicator' taxa with an important role in structuring communities, and propose hypotheses on the factors that shape bacterial biogeography that have been overlooked in the past.

This article has been accepted for publication and undergone full peer review but has not been through the copyediting, typesetting, pagination and proofreading process, which may lead to differences between this version and the Version of Record. Please cite this article as

No abstract