Climate change will alter precipitation patterns with consequences for soil C cycling. An understanding of how fluctuating soil moisture affects microbial processes is therefore critical to predict responses to future global change. We investigated how long‐term experimental field drought influences microbial tolerance to lower moisture levels (“resistance”) and ability to recover when rewetted after drought (“resilience”), using soils from a heathland which had been subjected to experimental precipitation reduction during the summer for 18 years. We tested whether drought could induce increased resistance, resilience, and changes in the balance between respiration and bacterial growth during perturbation events, by following a two‐tiered approach. We first evaluated the effects of the long‐term summer drought on microbial community functioning to drought and drying–rewetting (D/RW), and second tested the ability to alter resistance and resilience through additional perturbation cycles. A history of summer drought in the field selected for increased resilience but not resistance, suggesting that rewetting after drought, rather than low moisture levels during drought, was the selective pressure shaping the microbial community functions. Laboratory D/RW cycles also selected for communities with a higher resilience rather than increased resistance. The ratio of respiration to bacterial growth during D/RW perturbation was lower for the field drought‐exposed communities and decreased for both field treatments during the D/RW cycles. This suggests that cycles of D/RW also structure microbial communities to respond quickly and efficiently to rewetting after drought. Our findings imply that microbial communities can adapt to changing climatic conditions and that this might slow the rate of soil C loss predicted to be induced by future cyclic drought.

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A major challenge in microbial ecology is linking diversity and function to determine which microbes are actively contributing to processes occurring in situ. Bioorthogonal non-canonical amino acid tagging (BONCAT) is a promising technique for detecting and quantifying translationally active bacteria in the environment. This technique consists of incubating a bacterial sample with an analog of methionine and using click-chemistry to identify the cells that have incorporated the substrate. Here, we established an optimized protocol for the visualization of protein-synthesizing cells in oligotrophic waters that can be coupled with taxonomic identification using Catalyzed Reporter Deposition Fluorescent in Situ Hybridization. We also evaluated the use of this technique to track shifts in translational activity by comparing it with leucine incorporation, and used it to monitor temporal changes in both cultures and natural samples. Finally, we determined the optimal concentration and incubation time for substrate incorporation during BONCAT incubations at an oligotrophic site. Our results demonstrate that BONCAT is a fast and powerful semi-quantitative approach to explore the physiological status of marine bacteria.

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Climate change is exposing high‐latitude systems to warming and a shift towards more shrub‐dominated plant communities, resulting in increased leaf‐litter inputs at the soil surface, and more labile root‐derived organic matter (OM) input in the soil profile. Labile OM can stimulate the mineralization of soil organic matter (SOM); a phenomenon termed “priming.” In N‐poor subarctic soils, it is hypothesized that microorganisms may “prime” SOM in order to acquire N (microbial N‐mining). Increased leaf‐litter inputs with a high C/N ratio might further exacerbate microbial N demand, and increase the susceptibility of N‐poor soils to N‐mining. We investigated the N‐control of SOM mineralization by amending soils from climate change–simulation treatments in the subarctic (+1.1°C warming, birch litter addition, willow litter addition, and fungal sporocarp addition) with labile OM either in the form of glucose (labile C; equivalent to 400 µg C/g fresh [fwt] soil) or alanine (labile C + N; equivalent to 400 µg C and 157 µg N/g fwt soil), to simulate rhizosphere inputs. Surprisingly, we found that despite 5 yr of simulated climate change treatments, there were no significant effects of the field‐treatments on microbial process rates, community structure or responses to labile OM. Glucose primed the mineralization of both C and N from SOM, but gross mineralization of N was stimulated more than that of C, suggesting that microbial SOM use increased in magnitude and shifted to components richer in N (i.e., selective microbial N‐mining). The addition of alanine also resulted in priming of both C and N mineralization, but the N mineralization stimulated by alanine was greater than that stimulated by glucose, indicating strong N‐mining even when a source of labile OM including N was supplied. Microbial carbon use efficiency was reduced in response to both labile OM inputs. Overall, these findings suggest that shrub expansion could fundamentally alter biogeochemical cycling in the subarctic, yielding more N available for plant uptake in these N‐limited soils, thus driving positive plant–soil feedbacks.

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Two patterns of bacterial growth response upon drying and rewetting (DRW) of soils have previously been identified. Bacterial growth can either start increasing immediately after rewetting in a linear fashion (“type 1” response) or start increasing exponentially after a lag period (“type 2” response). The effect of repeated DRW cycles was studied in three soils with different response patterns after a single DRW cycle (“type 1”, “type 2” with a short lag period and “type 2” with a long lag period). The soils were exposed to seven DRW cycles, and respiration and bacterial growth were monitored after 1, 2, 3, 5, and 7 cycles. Exposure to repeated DRW shifted the bacterial growth response from a “type 2” to a “type 1” pattern, resulting in an accelerated growth recovery to a pre-disturbance growth rate. Bacterial growth in soils that initially had a “type 1” response also tended to recover faster after each subsequent DRW cycle. The respiration patterns after DRW also indicated the same transition from a “type 2” to a “type 1” pattern. Our results show that exposure to repeated DRW cycles will shape the bacterial response to future DRW cycles, which might be mediated by a shift in species composition, a physiological adjustment, evolutionary changes, or a combination of the three.

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