FEMS Microbiology Ecology Advance Access published December 8, 2014

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Title: Ammonia-oxidizing archaea respond positively to inorganic nitrogen addition in desert

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soils

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Authors: Yevgeniy Marusenko1*, Ferran Garcia-Pichel1, Sharon J. Hall1

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Affiliation: 1School of Life Sciences, Arizona State University, Tempe, AZ, 85287

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Correspondence: *Yevgeniy Marusenko, 602-703-7984, [email protected]

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Current address: 3312 Biological Sciences III,

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University of California, Irvine, CA, 92697, USA

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Abstract

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In soils, nitrogen (N) addition typically enhances ammonia oxidation (AO) rates and increases

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the population density of ammonia-oxidizing bacteria (AOB), but not that of ammonia-oxidizing

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archaea (AOA). We asked if long-term inorganic N addition also has similar consequences in

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arid land soils, an understudied yet spatially ubiquitous ecosystem type. Using Sonoran Desert

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top soils from between and under shrubs within a long-term N-enrichment experiment, we

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determined community concentration-response kinetics of AO and measured the total and

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relative abundance of AOA and AOB based on amoA gene abundance. As expected, N addition

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increased maximum AO rates and the abundance of bacterial amoA genes compared to the

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controls. Surprisingly, N addition also increased the abundance of archaeal amoA genes. We did

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not detect any major effects of N addition on ammonia-oxidizing community composition. The

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ammonia-oxidizing communities in these desert soils were dominated by AOA as expected (78%

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of amoA gene copies were related to Nitrososphaera), but contained unusually high contributions

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of Nitrosomonas (18%) and unusually low numbers of Nitrosospira (2%). This study highlights

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unique traits of ammonia-oxidizers in arid lands, which should be considered globally in

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predictions of AO responses to changes in N availability.

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Introduction

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Since the early and influential work of Sergei Winogradsky (1890), bacteria were thought to be

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the only biological agents of ammonia oxidation (AO). However, the deployment of molecular

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detection techniques in the last three decades has revealed that Thaumarchaeota in the Archaea

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domain contribute to AO as well (Konneke et al., 2005). High-throughput sequencing and

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molecular-fingerprinting studies show the presence of genes attributable to diverse groups of

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ammonia-oxidizing archaea (AOA) and bacteria (AOB) in a wide variety of environments

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(Purkhold et al., 2000; Leininger et al., 2006; Prosser & Nicol, 2008; Pester et al., 2012). Even

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though AOA outnumber AOB in many ecosystems (Leininger et al., 2006; Adair & Schwartz,

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2008; Wessen et al., 2010), this dominance does not always equate to AOA contributing to AO

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more than AOB (Jia & Conrad, 2009; Di et al., 2009; Adair & Schwartz, 2011). It remains

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unclear why the abundance of AOA is often unrelated to AO rates (Shen et al., 2008; Wessen et

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al., 2010). AO fluxes may depend not only on population size, but also on community

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composition due to differential substrate affinities and ecophysiological sensitivities among and

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within the AOA and AOB (Kowalchuk & Stephen, 2001; Bollmann et al., 2002; Schleper &

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Nicol, 2010).

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A review of literature reveals that mixed ammonia-oxidizer communities are often dominated by

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one particular phylotype (Prosser, 1989; Kowalchuk & Stephen, 2001; Zhalnina et al., 2012; He

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et al., 2012). However, it is uncertain if and how this outcome is determined by environmental

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properties. For instance, while culture work shows that Nitrosomonas strains (AOB) prefer

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ammonia-rich conditions (Taylor & Bottomley, 2006), Nitrosospira-related clusters (AOB)

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commonly outnumber Nitrosomonas spp. in fertilized soils and also in low-NH4+, pristine soils 3

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(Jordan et al., 2005; Chu et al., 2007). Additionally, AOB are preferentially enriched after

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inorganic nitrogen (N) fertilization in the ecosystems studied to date – such as in relatively low-

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pH soils that receive high rates of precipitation or water inputs – while AOA may respond

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positively only in cases when NH3/NH4+ is supplied through organic matter mineralization (Offre

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et al., 2009; He et al., 2012; Hatzenpichler, 2012; Levicnik-Hofferle et al., 2012). These

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examples suggest that indeed changes in N availability such as through N deposition or

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fertilization may control AO rates in soils through community compositional shifts (Avrahami &

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Bohannan, 2007; Tourna et al., 2010; Prosser & Nicol, 2012).

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Arid environments are vastly underrepresented in the AO research literature (Johnson et al.,

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2005; Marusenko et al., 2013b; Sher et al., 2013), but there is reason to believe that arid lands

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may harbor populations with different adaptations compared to the more studied temperate soils.

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For example, arid soils are exposed to prolonged drought and rapid pulses of precipitation and

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nutrients (Schimel et al., 2007; Collins et al., 2008), which require complex and fast genetic

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regulation from soil microbes (Rajeev et al., 2013). Furthermore, arid soils are often alkaline and

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can reach up to 50°C in the summer. They are typically dry with low organic matter content and

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low N mineralization rates especially in non-vegetated areas between shrubs (Austin et al.,

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2004; Schade & Hobbie, 2005), which may select for the most oligotrophic of ammonia-

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oxidizers. These ubiquitous soils also experience intensive management, including watering and

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fertilizer inputs, both in agricultural and urban residential areas (Warren et al., 1996; Davies &

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Hall, 2010). As a result, anthropogenic activities and atmospheric deposition are altering

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resource availability and the N cycle in soils of water-limited environments (McCrackin et al.,

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2008; Hall et al., 2009; Hall et al., 2011; Marusenko et al., 2013a).

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Here we tested the effect of long-term inorganic N addition on AO processes and ammonia-

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oxidizing microorganisms (AOM) in arid land soils, assessing the AO kinetics in bulk soil and

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characterizing AOA and AOB by sequencing the environmental amoA gene, which encodes a

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subunit of the ammonia-monooxygenase (AMO) enzyme. We hypothesized that N addition

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would cause the absolute and relative abundance of ammonia-oxidizers to shift from AOA-

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dominated in oligotrophic native (unfertilized) soils to AOB-dominated in NH4+-rich conditions,

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as has been found in other soils. Consequently, this population replacement would enhance

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overall AO rates and cell-specific AO rates, but decrease affinity between the enzyme and the

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substrate. Using common patch types in arid lands, we further expected that the decline of AOA

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relative to AOB under N addition would be less dramatic in relatively fertile soils under shrubs

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than in areas away from plants.

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Materials and Methods

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Study area description

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Our site is in the northern Sonoran Desert at ~620 m elevation in Lost Dutchman State Park, AZ,

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USA (coordinates: N 33.459372 S -111.484956), located east of the Phoenix metropolitan area

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and within boundaries of the Central Arizona–Phoenix Long-Term Ecological Research area

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(http://caplter.asu.edu). Soils are classified as Typic Haplargids, a subgroup of Aridisols. We

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measured soil AO rates and community parameters from two randomly assigned 20 m x 20 m

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plots, one that received N fertilizer as NH4NO3 (applied as solid by hand biannually at 60 kg N

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ha-1 yr-1 from 2005-2012) and another that served as an unfertilized control (see Hall et al., 2011

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for further description about the plots). Nitrogen deposition in this area is 7.3 kg N ha-1 yr-1

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(Cook, 2014). Plant cover (~60%) within our study plots is dominated by the native shrubs

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creosote bush (Larrea tridentata [DC.] Coville), bursage (Ambrosia spp.). Plots did not contain

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any N-fixing trees. Mean annual temperature is 22.3°C, with the coldest and warmest months

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averaging 3.7°C and 41.9°C, respectively (2005-2012; NCDC, 2013). Mean annual precipitation

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is 272 mm but is highly variable year to year. Rainfall is bimodally distributed between summer

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monsoon events and low-intensity winter storms (WRCC, 1985).

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Sample collection

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Surface soil samples were collected in late January of 2012, one month after winter storms. In

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each of the control and N addition plots, three soil samples were collected from each of two

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patch types to explore N treatment effects in typical desert environments: between plants

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(hereafter called 'interplant') and under canopies of the common shrub L. tridentata ('under

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plant'). Mature/dark soil biological crusts were low in abundance within the plot area and were

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avoided for sampling. Early colonization by biocrust organisms is widespread in the region

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(Rosentreter et al., 2007) but is not yet formed to visibility at our site locations. Each soil sample

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consisted of two 0-5 cm (depth) x 7 cm (diameter) cores taken 5 cm apart. In total, we collected

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twelve soil samples consisting of three replicate soil samples from each plot (treatment, control)

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and patch type (interplant, under plant) (3x2x2 = 12 samples). Soil samples were processed

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independently for all analyses (soil properties, AO rates, quantitative PCR, pyrosequencing).

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Laboratory methods and soil properties

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Following collection, samples were transported on ice to the lab, sieved to < 2 mm, and

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homogenized. Soils were at 3-5% soil moisture upon collection and were analyzed within 24 h

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for all soil properties and processes. Two subsamples (2 g each) from each homogenized soil

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sample were frozen in liquid N and stored at -80oC until DNA extraction within one month.

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Duplicate DNA extracts were combined prior to molecular processing methods to obtain one

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determination per sample.

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Soils were processed for pH (1:2 soil to DI H2O), water holding capacity (% WHC;

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gravimetrically), organic matter content (% SOM; loss on ignition), and extractable NH4+, nitrite

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(NO2-), and nitrate (NO3-) content (2M KCl extraction, colorimetric analysis), following standard

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methods (Sparks et al., 1996; Marusenko et al., 2013a). Data reported for each of the three field

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replicates is an average of laboratory triplicates.

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Ammonia oxidation rates using the shaken-slurry assay

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In situ net rates of potential AO were measured under various levels of N addition (see

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“Ammonia oxidation kinetics” below) using the shaken-slurry method (hereafter as “slurry AO

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rates”), in which oxygen and substrate diffusion is not limiting (Hart et al., 1994; Norton & Stark

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2011). The direct product of AO was measured as NO2- accumulation after inclusion of chlorate

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(NaClO3), a NO2--oxidation inhibitor (Belser & Mays 1980). Using NO3 - as a proxy for AO was

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unsuitable since NO2- build-up is common in natural dryland conditions (Gelfand & Yakir 2008).

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The shaken-slurry assays contained 10 g soil in 100 mL solution of 0.015 mol·L -1 NaClO3, and

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0.2 mol·L-1 K2HPO4 and 0.2 mol·L-1 KH2PO4 to buffer pH at 7.2. Slurries and no-soil blanks

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were continuously aerated in solution by mixing at 180 rpm on a reciprocal shaker in the dark.

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Homogenized slurry aliquots were removed at four time points over 6 h and amended with

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several drops of MgCl2 + CaCl2 (0.6 M) to flocculate soil particles. Aliquots were then

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centrifuged at 3000 × g and supernatant was filtered through pre-leached Whatman #42 ashless

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filters. The supernatants were stored at 4°C and analyzed within 24 h. Net rates of slurry AO

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were calculated as the linear increase in NO2- content from 0 to 6 h, measured colorimetrically

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using a Lachat Quikchem 8000 autoanalyzer. Consistent with literature showing that metabolism

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of ammonia oxidizers can be activated and responsive to the environment at the scale of hours,

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especially for AOB (Wilhelm et al., 1998; Placella & Firestone 2013), NO2- accumulation in our

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assays was linear from 0 to 6 h.

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Ammonia oxidation rates in static incubation

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As a secondary method to slurry AO rates, we also measured AO following various levels of N

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addition in a modified method using NaClO3 inhibition in static, 48 h aerobic incubations of bulk

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soil (“static AO rates” from here on; Nishio & Fujimoto 1990; Hart et al., 1994; Low et al.,

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1997). Although substrate diffusion may be limited in aerobic incubations to fully quantify

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enzyme activity, we used this method to independently assess AO in conditions more

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representative of the upland desert environment compared to the shaken-slurry assays, which

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assesses aerated AO potential. Ten g of soil were brought to 60% WHC using water and NaClO3

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(15 mM) in plastic cups. Soil in one cup was extracted at the onset and a second cup extracted

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after incubation for 2 days in the dark. Soils were extracted in 50 mL of 2 M KCl followed by

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shaking for 1 h and filtering through pre-leached Whatman #42 ashless filters. The extracts were

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stored at 4°C and analyzed colorimetrically within 24 h. Net rates of static AO were calculated

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as the increase in NO2- content between 0 and 48 h.

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Ammonia oxidation kinetics

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The relationship between substrate availability and reaction rate can be measured to discern

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functional parameters of microbial communities. Although this is not a true enzyme kinetics

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study, we applied similar calculations to our concentration-response kinetics approach to model

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relationships for AO (slurry and static) in bulk soils based on the Michaelis-Menten equation

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(Martens-Habbena & Stahl 2011; Prosser & Nicol 2012), as has been successfully applied to soil

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assays (Koper et al. 2010):

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V = (Vmax × S) / (Km + S)

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In this equation, the NH4+ concentration (S) and AO rate (V) are used to estimate the maximum

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AO rate (Vmax) and half-saturation constant (Km; inverse of enzyme and substrate affinity). To

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estimate AO kinetics under oligotrophic conditions in the shaken-slurry assay, we removed pre-

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existing NH4+ from soils to obtain the least variable and lowest residual substrate availability

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(Widmer et al., 1989; Koper et al., 2010; Norton & Stark 2011). Prior to the shaken-slurry assay,

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5 g soil was mixed in 45 mL of potassium phosphate solution and centrifuged at 3200 × g for 1

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min before discarding the N-containing supernatant. The resulting soil pellet from two

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preparations was combined to compose 10 g total soil from each plot (treatment, control), patch

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type (interplant, under plant), and soil sample replicate (x 3). Inorganic N was then supplemented

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as (NH4)2SO4 mixed with DI water to eight final concentrations in the slurry ranging from 0-22.5

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mM. In total we evaluated AO rates using 96 different soil preparations (12 soil samples x 8

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NH4+ concentrations) per method (shaken-slurry assay, static incubation). In the static

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incubations, we excluded the N removal step as to minimize soil disturbance. Soils were

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supplemented with (NH4)2SO4 in solution to produce final concentrations ranging from 0-50 µg

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NH4+-N g-1 (0-22.5 mM). The 0 µg NH4+-N g-1 addition (only includes pre-existing NH4+) was

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used to estimate background net rates of AO. As a rough indicator of the N addition effect on the

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relative importance of NH4+ mineralization and nitrification, we also measured the net rate of

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NH4+ gain (production processes dominate) and loss (consumption processes dominate) during

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the static incubation experiment. In the assay, some of the NH4+ consumption processes are

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likely minimized due to sieving of soil (exclusion of large NH4+-assimilating plant roots) and

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lower laboratory temperature compared to natural conditions (reduced volatilization).

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DNA extraction and purification

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DNA was extracted using three freeze-thaw cycles followed by 30 min incubation at 50°C with

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proteinase K and silica bead beating for chemical and mechanical cell lysis (Garcia-Pichel et al.,

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2001). The lysate was purified by phenol:chloroform:isoamyl alcohol (25:24:1) extraction,

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followed by DNA precipitation in 100% ethanol for 12 h at -80°C. DNA concentration and

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quality was assessed on an agarose gel stained in ethidium bromide and imaged using a Fluor-S

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Multi-Imager (BioRad Laboratories, CA, USA) with an EZ Load Precision Molecular Mass

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Standard (BioRad). Bands of DNA were excised from a low-melt agarose gel, homogenized with

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a tip in a microcentrifuge tube, allowed to diffuse out into sterile H2O for 12 h, and followed by

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15 min centrifugation to collect DNA in the supernatant.

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Quantitative PCR

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DNA was used for quantitative PCR (qPCR) with the following amoA primers: CrenamoA616r

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(GCCATCCABCKRTANGTCCA; Tourna et al., 2008) and CrenamoA23f for the AOA

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(ATGGTCTGGCTWAGACG); and amoA1f mod (GGGGHTTYTACTGGTGGT; Stephen et

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al., 1999) and AmoA-2R’ for the AOB (CCTCKGSAAAGCCTTCTTC; Okano et al., 2004;

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Junier et al., 2008). qPCR reactions contained 10 µL iTaq SYBRGreen Master Mix (BioRad),

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250 nM final concentration of each primer (AOA or AOB), 1 ng of environmental DNA, and

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molecular grade H2O to bring each reaction to a final volume of 20 µL. The reaction conditions

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were as follows: initial denaturation for 150 s at 95°C followed by 45 cycles of 15 s at 95°C, 30 s

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at 55°C, and 30 s at 72°C, and a final dissociation step to obtain the melting curve at 95°C, 60°C,

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and 95°C for 15 s each. Standard curves were generated using templates from Nitrosomonas

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europaea ATCC 19718 (bacterial amoA; R2 = 0.99) and a putative AOA clone (archaeal amoA;

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R2 = 0.99) for a dilution series spanning 102-1010 gene copies per reaction. Melting curves were

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checked to verify the quality of each reaction, and to ensure the absence of primer-dimers. We

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report only determinations for which Ct values could be interpolated within our standard curves.

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Each amoA abundance value (number of gene copies) reported is an average of analytical

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triplicate qPCR reactions of the same DNA extract.

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Pyrosequencing

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Purified DNA extracts were shipped to a commercial laboratory for standard PCR and bTEFAP

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pyrosequencing (Dowd et al., 2008). Commercial primers for PCR were amoA-1F

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(GGGGTTTCTACTGGTGGT; Rotthauwe et al., 1997) and amoA-2R for AOB

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(CCCCTCKGSAAAGCCTTCTTC), and Arch-amoAF (STAATGGTCTGGCTTAGACG;

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Francis et al., 2005) and Arch-amoAR for AOA (GCGGCCATCCATCTGTATGT) used with a

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HotStarTaq Plus Master Mix Kit (Qiagen, CA, USA). PCR conditions were as follows: 180 s at

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94°C followed by 28 cycles of 30 s at 94°C, 40 s at 53°C, and 60 s at 72°C, and final elongation

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for 5 min at 72°C. PCR amplicons were mixed in equal concentrations and purified using

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Agencourt Ampure beads (Agencourt Bioscience Corporation, MA, USA). Sequencing utilized

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Roche 454 FLX titanium instruments and reagents.

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Bioinformatics and phylogenetic analyses of amoA

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Pyrosequencing data were processed and analysed in Qiime (Caporaso et al., 2010b), with

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necessary pipeline adjustments to process functional gene data (i.e., amoA) as described in detail

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in the notes and script file (http://www.yevmarusenko.com/research/Marusenko_Qiime.txt).

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Sequences (452 bp long) were clustered into operational taxonomic units (OTUs) using UClust

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(Edgar, 2010). Representative sequences (one per OTU) were aligned with Pynast (Caporaso et

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al., 2010a). Based on nomenclature classification for AOA in Pester et al. (2012) and for AOB in

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Koops et al. (2006), a taxonomic assignment was made for each OTU using a template reference

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database created from sequences of known pure isolates, enrichments, and other characterized

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AOA and AOB from previous studies (reference database available at website mentioned above).

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Groups of sequences were clustered at 97% nucleotide similarity to be inclusive of OTUs at fine

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levels of resolution for phylogenetic and statistical analyses that otherwise may be missed at

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lower identity thresholds. For AOA, we excluded one replicate each in the interplant control and

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N addition samples because of their poor quality of the pyrosequencing data. The minimum

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number of high-quality sequences after filtering was 525 for AOA and 950 for AOB, with

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sufficient rarefied analysis producing 179 OTUs for AOA and 325 OTUs for AOB (Total

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number of sequences >200bp prior to quality filtering: AOA, 9,830; AOB, 29,569). Phylogenetic

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analyses were carried out on a single alignment file (separately for AOA and AOB) that included

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sequences from our Qiime pipeline, as well as the reference sequences described above. All

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sequences were combined and realigned using default parameters for Muscle and analyzed by

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the tree-building module of the MEGA 5 software with the following parameters: Neighbor-

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joining method, Jukes-Cantor nucleotide substitution model, 100 bootstrap replicates, uniform

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rates among sites, and pairwise gap-data deletion (Tamura et al., 2011). Raw sequence reads for

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the entire project have been deposited in the Sequence Read Archive (SRA) at NCBI with

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accession number SRSRX738968 for the AOA data and SRX739281 for the AOB data.

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Statistics

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Statistical tests were carried out using Qiime for α and β diversity measures on processed

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pyrosequencing data, while all other analyses were in SPSS (v20.0 Windows). All soil

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properties, AO rates, and amoA abundance data were tested for linear model assumptions in

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SPSS using normal probability plots (for normality) and Levene’s test (for equal variance), and

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transformed (natural log) when necessary. Individual two-way analysis of variance (ANOVA)

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tests were used to evaluate the effects of plants (‘Patch’) and N addition (‘Treatment’) on the

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following dependent variables: amoA gene abundance (per g soil and per ng extractable DNA,

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separately for AOA and AOB), AOA to AOB ratio, slurry Vmax AO rates, static Vmax AO rates,

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amoA-copy specific AO rates, net NH4+ change (averaged across supplemented NH4+

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concentrations), and each of the soil properties. Significant interactions between patch and

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treatment were evaluated further using one-way ANOVA (α = 0.025). The copy specific rates

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were calculated using Vmax AO rate (slurry and static) divided by the number of amoA gene

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copies per g soil. We used bivariate Pearson correlations to assess relationships between soil

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properties vs. community parameters (amoA data and AO rates) across all samples. We used

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linear regression analyses to assess relationships between amoA gene abundance at the domain

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level vs. Vmax AO rates and also analyzed amoA gene abundance of individual OTUs vs. soil

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properties and AO rates. In Qiime, we tested for the effect of N addition on OTU-based

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communities separately for AOA and AOB per patch type, using only strictly relevant diversity

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metrics (Lozupone & Knight, 2005; Caporaso et al., 2010b): α diversity (Shannon’s diversity,

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observed richness, and phylogenetic diversity [PD]) and β diversity (weighted and unweighted

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Unifrac, the multivariate group dispersion analogue of Levene's test [PERMDISP], and analysis

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of similarity [ANOSIM]).

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Results

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Effects of N addition on the abundance of amoA genes and the kinetics of ammonia oxidation

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To aid in interpretation of long-term N addition effects on amoA gene abundance and AO rates,

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we considered the influence of soil properties and the relative importance of fertilizer N vs.

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ammonification as a possible NH4+ source. Long-term N addition clearly resulted in an

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accumulation of NO2 -, NO3-, and NH4+, regardless of patch type (Table 1). Also as expected, soil

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organic matter was higher in soil under plants than between plants. N addition slightly acidified

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these alkaline soils – an effect known to worsen conditions for AO (Arp & Stein, 2003) – and yet

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AO rates still increase in these N-amended desert plots (Suppl. Table 1). Both types of AO rates

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we measured (maximum static and slurry AO rates) were strongly predicted by pH (negative

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correlation) and soil organic matter (positive correlation). Background AO rates measured in

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unamended incubations, however, were most strongly and positively related to NH4+

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concentration across all patch types and N treatments. Additionally, N addition significantly

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increased net rates of NH4+ loss in both interplant and under plant patch types (Patch, P = 0.56;

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Treatment, P < 0.01). These data suggest that N addition stimulated NH4+ loss from consumption

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processes (e.g., NH3/NH4+ oxidation, microbial immobilization) relatively more than it increased

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NH4+ concentrations from organic N mineralization.

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Surprisingly, N addition increased abundance of archaeal amoA genes compared to controls,

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regardless of the measure used (copies per g-1 soil, Fig. 1; or copies per total community DNA,

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904 vs 548 archaeal amoA copies/ng DNA; in soils between plants). As expected from many

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other studies, long-term N addition also increased the abundance of bacterial amoA gene copies.

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Fertilization decreased the AOA to AOB ratio in the relatively fertile soils under plant canopies

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(Fig. 1; Suppl. Table 2; N addition, 3.6 AOA/AOB; Control, 4.9 AOA/AOB) but generally

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increased it in the interplant soils (N addition, 6.2 AOA/AOB; Control, 4.3 AOA/AOB).

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Slurry maximum AO rates (i.e., at Vmax) were significantly higher after long-term N addition

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compared to those of the control soils (Fig. 2; P < 0.05 in both cases). This trend was also

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supported by measurements of static maximum AO rates (Suppl. Fig. 1; P < 0.05 in both cases).

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NH4+ supplementation only enhanced AO rates in the static incubations of unfertilized soils but

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not in fertilized soil (Suppl. Fig. 1), nor in any slurried incubations. These patterns show that

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rates of AO under undisturbed, unamended conditions are NH4+-limited and may be influenced

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by anthropogenic N additions. Taken together with the microbial abundance data, these results

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suggest that at least some of the AOA and AOB are likely contributors to AO (Suppl. Fig 2) and

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– as shown by the significant increases of AO rates as well as the abundance of archaeal and

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bacterial amoA genes after N addition – both archaeal and bacterial ammonia-oxidizers are

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responsive to environmental change.

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To investigate the functional capacity of ammonia-oxidizing communities in bulk soils, we

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evaluated the affinity (Km) parameter from the AO kinetics plots (Fig. 2; Suppl. Fig. 1). Km was

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not possible to estimate formally in the shaken slurry assays since rates were always close to

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maximum regardless of supplemental N addition, highlighting the low ammonia demand of

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ammonia-oxidizers in desert soils. Residual NH4+ as low as 17 µM were measured in these

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assays (Fig. 2), implying that the community Km is likely at or below this low value, which is

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significantly lower than typical Km values for known AOB cultures (see rates compiled in

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Martens-Habbena et al., 2009). In the intact incubations that were not continuously aerated

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(static AO rates; Suppl. Fig. 1), the mean Km was 2.6 mM for control soils under plants and 1.2

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mM for the control soils between plants. Effects of N addition could not be evaluated, given that

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the long-term N addition itself prevented incubations at low enough ammonium.

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An alternative way of looking at differential efficiency in ammonium utilization is to normalize

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the maximum AO rate by the size of the community (Fig. 3; Suppl. Fig. 3). Here, AO was more

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efficient (higher rates per copy of amoA gene) under plants than between plants (P < 0.05 in all

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cases), and long-term N addition led to more efficient rates of AO compared to control soils in

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the spaces between plants (significant for the shaken-slurry assay; Fig. 3; P < 0.001; Fig. 3;

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Suppl. Fig. 3). These results suggest a change in community function (NH3 processed per amoA),

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given that the ammonia-oxidizing community adapted favorably to higher nutrient soils (e.g.,

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under plants and N addition).

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Composition of the ammonia-oxidizing community

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All phylotypes detected were related to either Nitrososphaera (Thaumarchaeota) or

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Nitrosomonas and Nitrosospira (both β-Proteobacteria), at a ratio of about 45:10:1, respectively

363

(Fig. 4; Fig. 5). Even though this ratio is subject to potential primer biases, choosing primers that

364

are unlikely to miss abundant AOM groups (Junier et al. 2008) helps to combine qPCR and

365

sequencing data for approximate abundance comparisons of phylotypes across domains. The

366

most abundant phylotype, belonging to the Nitrososphaera subcluster 1.1, accounted for 60% of

367

all the amoA sequences. The community composition was minimally influenced by patch type or

368

N addition treatment, when assessed at the level of OTUs, and we could not detect any

369

significant differences in the relative abundance of the dominant members (Fig. 4). In soil under

370

plants, N addition decreased AOA phylogenetic diversity (PD) (P < 0.001) but increased the

371

within-group variance for AOB (PERMDISP analysis, P = 0.037), suggesting that N addition has

17

372

distinct effects on community relatedness of the AOA than of the AOB. However, all other α and

373

β diversity metrics revealed that the structure of AOA and AOB was not influenced by N

374

addition or patch type (P > 0.1 in all cases). Together – at least as far as one can detect based on

375

the amoA gene sequences – these data suggest that long-term N addition had a minor effect, if at

376

all, on AOA and AOB community structure.

377 378

Discussion

379 380

Source of N for ammonia-oxidizers

381 382

Many studies from various non-arid ecosystems have shown that inorganic N addition either

383

does not affect AOA or allows AOB to outcompete AOA (e.g., Jia & Conrad, 2009; Di et al.,

384

2009; Stopnisek et al., 2010; Xia et al., 2011; Levicnik-Hofferle et al., 2012; and reviewed in

385

Hatzenpichler, 2012). A few studies have shown that AOA may react favorably to NH3

386

originating from organic N sources or N mineralization (Chen et al., 2008; Schauss et al., 2009;

387

Kelly et al., 2011; Lu et al., 2012; Levicnik-Hofferle et al., 2012; Daebeler et al., 2012). Studies

388

showing an increase in AOA abundance after inorganic N additions are rare (Verhamme et al.,

389

2011; Daebeler et al., 2014; current study). The positive response by AOA may be explained by

390

NH3 availability from organic N or mineralization from organic sources (He et al., 2012).

391

However, organic N inputs are relatively low in ecosystems such as deserts and other extreme

392

environments (Schimel & Bennett, 2004; Booth et al., 2005). Although N inputs to arid lands

393

significantly increase productivity and N content of seasonal herbaceous annual plants, net

394

potential N mineralization in soil does not appear to be consistently augmented by N addition –

18

395

perhaps due to the frequency of water limitation, the patchiness of plant growth, and organic

396

matter loss pathways such as photodegradation and aeolian/hydrologic transport (Hall et al.,

397

2009; Rao et al., 2009; Hall et al., 2011). Regardless of the role of organic N, our results

398

highlight the unique, positive response of AOA to long-term inorganic N addition in the low

399

organic matter plant interspaces of desert soils.

400 401

The use of inorganic N fertilizers by AOA may be plausible in arid systems. Since heterotrophs

402

are likely the first to consume organic N upon metabolic activation after drought, the typical

403

pulses of resource availability imparted by fast drying/wetting cycles may force AOA to utilize

404

NH3 from inorganic N sources (Placella & Firestone, 2013). Additionally, alkaline and hot

405

environments may enhance NH4+ deprotonation, leading to NH3-gas diffusion throughout the soil

406

matrix (McCalley & Sparks, 2009; Geisseler et al., 2010). The same strains of AOA may be

407

capable of using either NH3 from organic N or inorganic N sources depending on environmental

408

conditions (He et al., 2012), as shown in vitro for the only pure AOA isolate from soil,

409

Nitrososphaera viennensis (e.g., urea; Tourna et al., 2011), and predicted in silico based on the

410

genome of a recent enrichment culture, Candidatus Nitrososphaera gargensis (Spang et al.,

411

2012).

412 413

Size, structure, and function of ammonia oxidizing communities in arid land soils

414 415

We hypothesized that long-term N addition selects for ammonia-oxidizers that are more

416

copiotrophic (lower substrate affinity, higher activity per amoA gene copy) than those in

417

unfertilized soils (Martens-Habbena et al., 2009; Prosser & Nicol, 2012). Indeed, N addition

19

418

elevated the AO rate per amoA–copy, but this effect was significant for only the least fertile parts

419

of the landscape (in soil between plants; Fig. 3) where the desert-adapted ammonia oxidizers

420

may be functioning differently after fluctuations in the environment. Differences in organic

421

compounds between soils under and away from vegetation may affect function of ammonia

422

oxidizers as it does in cultures (Lehtovirta-Morley et al., 2014). However, the relative abundance

423

of dominant amoA OTUs was constant across treatments, with small changes only in the minor

424

members (Fig. 4). Of course we cannot fully discount the idea that perhaps the minor OTUs

425

represent those that are ecologically relevant, while the numerically dominant groups are less

426

efficient or inactive (Lennon & Jones, 2011). This scenario has yet to be proven experimentally

427

and is unlikely to be the case here since archaeal and bacterial amoA gene abundance – largely

428

determined by the common OTUs – was positively correlated with AO rates (Suppl. Fig. 2).

429 430

Evidence of unique ammonia oxidation patterns in deserts

431 432

Arid land soils face extreme environmental conditions that may select for unique phylogeny and

433

niche separation. Terrestrial studies worldwide have revealed that the “marine” clade AOA

434

(Group I.1a) are often the main contributors to AO and responders to changes in conditions from

435

soil incubations (Hatzenpichler, 2012), despite being outnumbered by the “soil” clade (Group

436

I.1b; Verhamme et al., 2011; Isobe et al., 2012; Long et al., 2012; Zhang et al., 2012; Lu & Jia,

437

2013). Here, we show that AOA within the “soil” clade responded significantly to N addition,

438

and the abundance of this group was positively related to AO rates in desert soil. We also found

439

that Nitrosomonas sequences outnumbered Nitrosospira, a rarity pattern for soil systems.

440

Wastewater discharge in a desert environment was found to harbor Nitrosomonas-like strains

20

441

(Angel et al., 2010), but is an unlikely scenario for the rural location of our soils in a protected

442

state park. Alternatively, dominance of many Nitrosomonas spp. appears to be limited to

443

alkaline, high-salt, and sometimes high-NH4+ conditions (Webster et al., 2005; Koops et al.,

444

2006; Cantera et al., 2006; Ke & Lu, 2012). Pulsed resource availability – a characteristic of arid

445

lands – may also drive this distribution, since Nitrosomonas strains have advantages over

446

Nitrosospira such as faster growth responses after starvation (Bollmann et al., 2002).

447

Additionally, in most soils studied previously, AOA outnumber AOB to a greater extent than

448

found in our study (Leininger et al., 2006). In the occasional cases where AOB outnumber AOA,

449

typically up to 10-fold in terrestrial systems (e.g., Di et al., 2009), other arid lands also have a

450

novel distribution as AOB outnumber AOA by 100-fold in cold desert biocrusts (Marusenko et

451

al., 2013b). Overall, atypical ammonia-oxidizing communities appear to occupy desert soils.

452 453

Growth and activity characteristics derived from culture experiments can be combined with

454

environmental data to explore relationships between AOA and AOB at the physiological and

455

ecosystem scale (Stark & Firestone, 1996; Schauss et al., 2009; Prosser & Nicol, 2012). For

456

example, since maximum AO activity per cell is higher for Nitrosospira and Nitrosomonas

457

strains than for AOA (10 and 35-fold, respectively), the contribution of AOB to our AO rates

458

must be much more important than could be predicted from their abundance. With a 10:1 ratio of

459

abundance between Nitrosomonas and Nitrosospira in our soils, the weighted average maximum

460

cell activity for Nitrosomonas plus Nitrosospira should be 33-fold higher than that of AOA.

461

Based on the assumption that 1 amoA copy exists per AOA cell, and that a weighted average of

462

2.1 amoA copies are found per AOB cell (2 and 3 amoA copies per cell for Nitrosomonas and

463

Nitrosospira, respectively; Norton et al., 2002), we can estimate that the maximum AO activity

21

464

per amoA copy is 16-fold higher for AOB than AOA in our soils. Assuming equal number of

465

genomes and level of transcription/translation of amoA, the fact that AOA amoA copies

466

outnumber AOB in our soils by 4.3-fold still means that AOB contribute 3.7-fold more than

467

AOA to overall AO rates. These calculations are consistent with our data, which show that AOB

468

contribute on average 4.5 times more to AO rates than AOA (compare slopes in Suppl. Fig. 2).

469

Even though AOB are the dominant contributors at the ecosystem scale (e.g., total AO), the

470

doubling of AOA abundance in soils between plants of N fertilized plots means that the relative

471

importance of AOB and AOA to AO may change with N increases. This type of study refines

472

predictions of how environmental conditions affect the link between community dominance and

473

AO rates.

474 475

Conclusion

476 477

N addition affects arid land N cycling primarily through changes in community size, but less so

478

through changes in community composition. This study shows significant and positive effects of

479

inorganic N addition on abundance of Nitrososphaera-related AOA in soils. This pattern has

480

been rarely shown before, especially where N inputs from organic sources are low such as in

481

unique conditions of desert soils. Increased anthropogenic activity resulting in environmental N

482

enrichment may continue to alter ecosystem function through responses by both the AOA and

483

AOB. This work stresses the importance of research in arid lands in that results from mesic

484

systems may not be readily applicable, particularly given that agricultural and pastoral systems in

485

drylands occupy ~32% of the terrestrial land surface worldwide and often contain alkaline soil

486

that is routinely exposed to high temperatures (Koohafkan & Stewart, 2008). These systems may

22

487

contain AOM communities more similar to hot deserts than to arable lands from more mesic

488

environments.

489 490

Our results highlight the effects of N enrichment on AO rates and the community size of

491

ammonia oxidizers. We explored patterns resulting from long-term N enrichment, yet it remains

492

to be seen whether population dominance also shifts during short-term N changes associated

493

with pulsed moisture fluctuations that are characteristic of arid lands. Seasonal changes may

494

occur in AO communities (e.g. AOA abundance may dominate relative to AOB in the summer;

495

Sher et al., 2013), but it is currently unclear whether these changes are related to rates of

496

nitrification in arid and semi-arid soils following long-term N additions (Hall et al., 2011).

497

Future work is essential to investigate how our results compare to those of other arid lands and at

498

scales that were not tested here. Further research is also necessary to predict the AOM

499

contribution to ecologically and atmospherically important gases such as N2O or NO from

500

nitrifier denitrification and nitrification in these desert soils.

501 502

Acknowledgements

503 504

We would like to thank David Huber, Jennifer Learned, Brenda Ramirez, Julea Shaw and Natalie

505

Myers for assistance with lab work and training. We are grateful to Jean McLain, Egbert

506

Schwartz, Estelle Couradeau, and Elizabeth Cook for manuscript review. This work is supported

507

by NSF through the CAP LTER program (grant BCS-1026865). Funding was also provided by

508

the NSF Western Alliance to Expand Student Opportunities (WAESO) program and the GPSA at

509

ASU. The authors declare no conflict of interest.

510 23

510 511

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764

Table 1. Soil characteristics from plots used in this study.

765 pH

WHC (%)a

SOM (%)b

Soil patch Treatmentd Mean SD Mean SD Mean SD typec Interplant

Control

Interplant N addition Under plant

Control

Under plant

N addition

NO2- (µg N·g-1)

NO3- (µg N·g-1)

Mean SD

Mean 1.40

SD 0.41

NH4+ (µg N·g-1) Mean

8.39 0.07 32.0 4.5

2.02 0.57

0.13 0.08

8.21 0.08 35.1 2.8

2.45 0.44

1.58 0.71

8.25 0.11 42.1 3.3

3.26 0.37

0.03 0.01

4.50

4.63

1.06

0.04

8.11 0.06 45.2 6.9

3.59 0.55

0.16 0.19

29.12

5.11

12.77

9.39

36.10 21.37

0.42

SD 0.17

22.47 21.31

Two-way ANOVA results, P value

Patch x Treatment Treatment Patch

0.651

0.992

0.868

0.171

0.459

0.464

0.007*

0.284

0.214

0.002*

0.002*

0.036*

0.034*

0.006*

0.003*

0.002*

0.772

0.519

766 767 768 769 770

a WHC = water holding capacity. b SOM = soil organic matter. c Soils were collected from spaces between plants or under the canopy of Larrea tridentata shrubs. d N addition plots were treated with 60 kg of N (as NH4NO3) ha-1·yr-1 during 2005-2012. Significance at α = 0.05 indicated by bold and *. SD = standard deviation. n = 3.

771 772

32

772

Figure legends

773 774

Figure 1. Quantification of amoA gene copy numbers for AOB and AOA from Sonoran Desert

775

soil in N addition and control plots. Error bars are standard errors of independent field triplicates.

776

33

776 777

Figure 2. Concentration-response kinetics of ammonia oxidation using the shaken-slurry assay

778

for net potential rates. To test the effect of long-term N addition on ammonia oxidation rates,

779

soils were supplemented with a range of NH4+ concentrations in the short-term laboratory

780

methods to measure kinetics of ammonia oxidation. NO2- accumulation is measured after sodium

781

chlorate inhibition as a proxy for ammonia oxidation. Bi-directional error bars are standard

782

deviations of independent field triplicates to show variation in supplemented NH4+ and measured

783

ammonia oxidation rates.

784

34

784 785

Figure 3. Effects of N addition on the function of the amoA gene-containing community using

786

estimates of copy-specific ammonia oxidation rates. Specific rates were calculated as maximum

787

ammonia oxidation rate (Vmax) from the shaken-slurry assay, divided by amoA gene copy

788

number per g soil. Error bars are standard errors of Vmax and amoA calculations for independent

789

field triplicates.

790

35

790 791

Figure 4. Community composition of OTUs (clustered at 97% nucleotide similarity) based on

792

bioinformatics of amoA gene pyrosequences. Diversity measures were analyzed separately for

793

AOA and AOB. Brackets include taxonomic classifications and percent of phylotype out of

794

AOA or AOB as an average across all treatment and patch replicates. The remaining 2% of AOB

795

were unclassified to the species-level. The remaining 2% of AOA are identified under

796

Nitrososphaera subclusters 2, 8, and 9. Despite biases with qPCR and pyrosequencing

797

technologies, the AOB and AOA bars are drawn at scale (about 25 and 75% of total amoA,

798

respectively). Each bar is the average of independent field and pyrosequencing triplicates

799

(excluding one replicate each in the interplant control and N addition samples for the AOA).

800

36

800 801

Figure 5. Neighbor-joining phylogenetic tree of archaeal and bacterial amoA gene sequences.

802

Sequences for this study were obtained from pyrosequencing of the amoA gene. Sequences of

803

known strains and subclusters are used as reference groups. OTUs were clustered at 97%

804

nucleotide similarity and taxonomy classified at multiple phylogenetic levels within the

805

Thaumarchaeota (formerly named Crenarchaeota) as proposed by Pester et al. (2012) and

806

within the AOB (Purkhold et al., 2000). The relative abundance of phylogenetic groups within

807

the AOA or AOB detected in this study is shown in parentheses next to the clade name. Height

808

of clades is proportional to the OTU richness. Bootstrap support is represented by full (75-99%)

809

and empty (50-75%) markers at the nodes.

810

37