Nitrogen (N) cycling in drylands under changing climate is not well
understood. Our understanding of N cycling over larger scales to date relies
heavily on the measurement of bulk soil N, and the information about internal
soil N transformations remains limited. The
Drylands cover approximately 41 % of the Earth's land surface and play an essential role in providing ecosystem services and regulating carbon (C) and nitrogen (N) cycling (Hartley et al., 2007; Poulter et al., 2014; Reynolds et al., 2007). After water, N availability is the most important limiting factor for plant productivity and microbial processes in dryland ecosystems (Collins et al., 2008; Hooper and Johnson, 1999). Despite low soil N mineralization rates, N losses are postulated to be higher relative to N pools in dryland ecosystems compared with mesic ecosystems (Austin, 2011; Austin et al., 2004; Dijkstra et al., 2012). However, we still lack a full understanding of the constraints on N losses in drylands because multiple processes contribute to N losses, and the response of those processes to changing climate is highly variable (Nielsen and Ball, 2015). The precipitation regimes in drylands are predicted to change during the 21st century (IPCC, 2013), and more extreme climatic regimes will make dryland ecosystems more vulnerable to enhanced drought in some regions and intensive rain in others (Huntington, 2006; Knapp et al., 2008). Therefore, improving our understanding of N cycling and its controls would greatly enhance our ability to predict the responses of dryland ecosystems to global changes.
The natural abundance of
Ammonium (NH
Soil microbes constitute a major portion of the biota in terrestrial
ecosystems and play key roles in regulating ecosystem functions and
biogeochemical cycles (van Der Heijden et al., 2008). Linking soil microbial
communities and N processes is critical for evaluating the response of N
transformations to climate changes. However, despite the rapid development of
high-throughput sequencing techniques in recent decades, there is still a
great challenge for researchers to establish such linkages due to technical
limitations, especially at large spatial scales (Zhou et al., 2011).
Alternatively, a microarray-based metagenomics technology, GeoChip, has been
developed for the analysis of microbial communities (He et al., 2007, 2010b;
Tu et al., 2014). This technique can be used not only to analyze the
functional diversity, composition, and structure of microbial communities but
also to directly reveal the linkages between microbial communities and
ecosystem functions (He et al., 2007). Functional gene microarray approaches
have been used to examine the response of microbially mediated N processes
under different environmental conditions. Denitrification genes from the
soils in Antarctica, for example, are associated with increased soil
temperatures, and N
Vegetation type and sampling site distribution along
the transect. Across the 3200 km precipitation gradient in northern China,
four typical vegetation types are distributed from west to east, which are
desert
In this study, we studied the effects of water availability on
ecosystem-level N availability and cycling along a 3200 km transect in
northern China. This natural gradient of precipitation provides an ideal
system for identifying the response of soil N dynamics to water availability.
In a previous study we reported a hump-shaped pattern of
The research was carried out along a 3200 km transect across Gansu Province
and Inner Mongolia in northern China, covering a longitude from 87.4 to
120.5
Soil sampling was conducted from July to August 2012, the peak of the plant
growing season. This is the same transect as described in Wang et al. (2014),
but with slightly different site coverage. We selected 36 sites at
approximately 100 km intervals between adjacent sites due to limited time to
extract soil with KCl solution on the same day after intensive sampling
(Fig. 1), whereas 50 sites at approximately 50 km intervals were used for
bulk soil N isotopes measurement in Wang et al. (2014). At each site, we set
a 50 m
Soil pH was measured using a pH meter and a soil-to-water ratio of
The analyses of the isotope compositions of NH
For soil DNA extraction, purification, and quantification and the analysis of
functional structure of soil microbial communities, we adopted the same
approaches as described previously (Wang et al., 2014). In addition to the
abundance of nitrification and denitrification genes reported in Wang et
al. (2014), the abundance of N fixation, ammonification, and anaerobic
ammonia oxidation (anammox) genes was included in this paper. Briefly,
microbial genomic DNA was extracted from 0.5 g soil using the MO BIO PowerSoil
DNA isolation kit (MO BIO Laboratories, Carlsbad, CA, USA) and purified by
agarose gel electrophoresis followed by phenol–chloroform–butanol extraction.
DNA quality was assessed by the A260/280 and A260/230 ratios using a NanoDrop
ND-1000 spectrophotometer (NanoDrop Technologies Inc., Wilmington, DE, USA), and
final soil DNA concentrations were quantified with PicoGreen using a FLUOstar
Optima (BMG Labtech, Jena, Germany). The GeoChip 5.0S, manufactured by
Agilent (Agilent Technologies Inc., Santa Clara, CA), was used for analyzing
DNA samples. The experiments were conducted as described previously (Wang et
al., 2014). In short, the purified DNA samples (0.6
All analyses were conducted using the software package SPSS 18.0 (SPSS,
Chicago, IL) for Windows. Pearson correlation analysis was conducted to
examine the linear relationships between different variables.
Independent-sample
We found significant inorganic N accumulation in the investigated soil layer
(0–10 cm) at sites with a MAP less than 100 mm (
In the arid zone, soil NO
Nitrogen concentrations and isotopic composition of bulk soil N,
NH
The
The N isotopic signature of NH
The relative
The abundances of microbial genes of five main N cycling groups (N fixation, ammonification, nitrification, denitrification, and anammox) were measured at all sites. In arid-zone soils, the abundances of all N cycling genes were extremely low (Fig. 4), indicating limited microbial potential in this very dry environment. A sharp increase (by eight- to ninefold) in the gene abundance was noted from the arid zone to the semiarid zone (Fig. 4), even though the soils were still mostly dry at the time of sampling (see soil moisture in Fig. S2). The gene abundances in the semiarid zone were 1 to 2 orders of magnitude greater than those in the arid zone. In addition, the microbial gene abundances of the five main N cycling groups all increased with increasing precipitation in both the arid and semiarid zones (Fig. 4), suggesting a potential effect of water availability on soil microbial N processes.
Changes in the abundance of microbial gene involved in N cycling. Signal intensity was standardized based on both the number of array probes and DNA quantity in a gram of dry soil. Each point is the site-averaged value; results of the abundance of nitrification and denitrification genes were reported in a previous study (Wang et al., 2014).
We observed different patterns of N cycling above and below a MAP threshold
of 100 mm along this 3200 km transect. In the semiarid zone, the increased
precipitation seemed to lead to increased losses of soil NO
Relationship between
In the arid zone, the
In contrast to the
Soil pH and the relationship with
In the semiarid zone, NH
Relationship between the
Unexpectedly, we detected high anammox gene abundance in these dryland
ecosystems (Fig. 4). Anammox is the microbial reaction between NH
Other abiotic processes have also been reported to contribute to N losses in
drylands. High soil surface temperature driven by solar radiation may be
responsible for gaseous N losses in dryland ecosystems (Austin, 2011;
McCalley and Sparks, 2009, 2008), and they may affect
We observed much higher concentrations of soil NO
In the semiarid zone, the
Ammonium accumulation was noted in the arid-zone soils and the accumulated
NH
A framework of N biogeochemical cycling in dryland ecosystems in
northern China. Width of arrows and size of boxes indicate the relative
importance (qualitative interpretation) of soil N processes and pools between
the arid zone
In the semiarid zone, soil NH
Our study reported the pattern of
In the arid zone, characterized by extreme aridity
(36 mm < MAP < 100 mm; Fig. 8a), plant cover was
sparse and microbial activity was limited (Figs. 1 and 4). Nitrogen input,
mostly in the form of atmospheric deposition, largely accumulated, creating
In the semiarid zone (100 mm < MAP < 436 mm; Fig. 8b),
controls on N cycling increasingly shift from abiotic to biotic factors.
Microbial gene abundances associated with N cycling groups were considerably
greater when water became more available (Fig. 4). Increasing N
mineralization with increasing MAP was accompanied by reduced NH
Yunting Fang, Dongwei Liu, Weixing Zhu, and Xingguo Han designed the study; Dongwei Liu, Xiaobo Wang, Yuepeng Pan, Chao Wang, Dan Xi, Yuesi Wang, and Xingguo Han performed the experiment; Dongwei Liu, Weixing Zhu, Yunting Fang, Xiaobo Wang, Yuepeng Pan, Chao Wang, Dan Xi, Edith Bai, and Yuesi Wang analyzed the data. Dongwei Liu, Weixing Zhu, and Yunting Fang wrote the paper; Xiaobo Wang, Yuepeng Pan, Chao Wang, Edith Bai, and Xingguo Han contributed to discussion of the results and paper preparation.
The authors declare that they have no conflict of interest.
This work was financially supported by the National Key Research and Development Program of China (2016YFA0600802), the Strategic Priority Research Program of the Chinese Academy of Sciences (XDB15020200, XDB15010401, and XDA05100100), the National Natural Science Foundation of China (31370464, 31422009, 41405144, and 31600358), Hundred Talents Program of the Chinese Academy of Sciences (No. Y1SRC111J6), and State Key Laboratory of Forest and Soil Ecology (LFSE2015-19). Liu was supported by the Chinese Scholarship Council (CSC) Fellowship to study in the USA. We would like to thank Ying Tu, Haiyan Ren, Shasha Zhang, Feifei Zhu, and Xiaoming Fang for their assistance in field sampling and laboratory analysis, and Shaonan Huang for sharing the unpublished data. We thank all members of the sampling team from the Institute of Applied Ecology, Chinese Academy of Sciences for their assistance during field sampling. We would like to thank Ben Eisenkop and Zhengjie Li for their assistance with the English editing. We also thank the reviewers and the editor for their helpful comments and constructive suggestions, which have greatly improved the quality of this paper. Edited by: M. Weintraub Reviewed by: F. Soper and three anonymous referees