Higher aridity and more extreme rainfall events in drylands are predicted due to climate change. Yet, it is unclear how changing precipitation regimes may affect nitrogen (N) cycling, especially in areas with extremely high aridity. Here we investigate soil N isotopic values (d 15 N) along a 3,200 km aridity gradient and reveal a hump-shaped relationship between soil d 15 N and aridity index (AI) with a threshold at AI ¼ 0.32. Variations of foliar d 15 N, the abundance of nitrification and denitrification genes, and metabolic quotient along the gradient provide further evidence for the existence of this threshold. Data support the hypothesis that the increase of gaseous N loss is higher than the increase of net plant N accumulation with increasing AI below AI ¼ 0.32, while the opposite is favoured above this threshold. Our results highlight the importance of N-cycling microbes in extremely dry areas and suggest different controlling factors of N-cycling on either side of the threshold.

BackgroundAlthough high-throughput sequencing, such as Illumina-based technologies (e.g. MiSeq), has revolutionized microbial ecology, adaptation of amplicon sequencing for environmental microbial community analysis is challenging due to the problem of low base diversity.ResultsA new phasing amplicon sequencing approach (PAS) was developed by shifting sequencing phases among different community samples from both directions via adding various numbers of bases (0–7) as spacers to both forward and reverse primers. Our results first indicated that the PAS method substantially ameliorated the problem of unbalanced base composition. Second, the PAS method substantially improved the sequence read base quality (an average of 10 % higher of bases above Q30). Third, the PAS method effectively increased raw sequence throughput (~15 % more raw reads). In addition, the PAS method significantly increased effective reads (9–47 %) and the effective read sequence length (16–96 more bases) after quality trim at Q30 with window 5. In addition, the PAS method reduced half of the sequencing errors (0.54–1.1 % less). Finally, two-step PCR amplification of the PAS method effectively ameliorated the amplification biases introduced by the long barcoded PCR primers.ConclusionThe developed strategy is robust for 16S rRNA gene amplicon sequencing. In addition, a similar strategy could also be used for sequencing other genes important to ecosystem functional processesElectronic supplementary materialThe online version of this article (doi:10.1186/s12866-015-0450-4) contains supplementary material, which is available to authorized users.

The relationship between biodiversity and ecosystem stability is poorly understood in microbial communities. Biofilm communities in small bioreactors called microbial electrolysis cells (MEC) contain moderate species numbers and easy tractable functional traits, thus providing an ideal platform for verifying ecological theories in microbial ecosystems. Here, we investigated the resilience of biofilm communities with a gradient of diversity, and explored the relationship between biodiversity and stability in response to a pH shock. The results showed that all bioreactors could recover to stable performance after pH disturbance, exhibiting a great resilience ability. A further analysis of microbial composition showed that the rebound of Geobacter and other exoelectrogens contributed to the resilient effectiveness, and that the presence of Methanobrevibacter might delay the functional recovery of biofilms. The microbial communities with higher diversity tended to be recovered faster, implying biofilms with high biodiversity showed better resilience in response to environmental disturbance. Network analysis revealed that the negative interactions between the two dominant genera of Geobacter and Methanobrevibacter increased when the recovery time became longer, implying the internal resource or spatial competition of key functional taxa might fundamentally impact the resilience performances of biofilm communities. This study provides new insights into our understanding of the relationship between diversity and ecosystem functioning.