Factors Driving Potential Ammonia Oxidation in Canadian ArcticEcosystems: Does Spatial Scale Matter?

Samiran Banerjee and Steven D. Siciliano

Department of Soil Science, University of Saskatchewan, Saskatoon, Canada

Ammonia oxidation is a major process in nitrogen cycling, and it plays a key role in nitrogen limited soil ecosystems such asthose in the arctic. Although mm-scale spatial dependency of ammonia oxidizers has been investigated, little is known about thefield-scale spatial dependency of aerobic ammonia oxidation processes and ammonia-oxidizing archaeal and bacterial commu-nities, particularly in arctic soils. The purpose of this study was to explore the drivers of ammonia oxidation at the field scale incryosols (soils with permafrost within 1 m of the surface). We measured aerobic ammonia oxidation potential (both autotrophicand heterotrophic) and functional gene abundance (bacterial amoA and archaeal amoA) in 279 soil samples collected from threearctic ecosystems. The variability associated with quantifying genes was substantially less than the spatial variability observed inthese soils, suggesting that molecular methods can be used reliably evaluate spatial dependency in arctic ecosystems. Ammonia-oxidizing archaeal and bacterial communities and aerobic ammonia oxidation were spatially autocorrelated. Gene abundanceswere spatially structured within 4 m, whereas biochemical processes were structured within 40 m. Ammonia oxidation wasdriven at small scales (<1m) by moisture and total organic carbon, whereas gene abundance and other edaphic factors droveammonia oxidation at medium (1 to 10 m) and large (10 to 100 m) scales. In these arctic soils heterotrophs contributed between29 and 47% of total ammonia oxidation potential. The spatial scale for aerobic ammonia oxidation genes differed from potentialammonia oxidation, suggesting that in arctic ecosystems edaphic, rather than genetic, factors are an important control on am-monia oxidation.

Approximately 13% of world’s total land area is underlain bypermafrost and in Canada permafrost-affected soils comprise

3.7 million km2 or ca. 40% of the land mass (67). These soil eco-systems differ from others due to their low annual mean temper-atures, long winters, short growing seasons, frequent cryoturba-tion (soil movement because of frost action), and gelifluction(slow downslope movement of waterlogged soil over permafrostlayer and formation of lobe-shaped features). A key feature ofthese arctic ecosystems compared to temperate ecosystems is thatsubstantial ammonia (as much as 14 mg m�2 NH4

�-N) is pro-duced over the winter period and the fate of this ammonia iscrucial to the productivity of the above ground ecosystems (8).Climate change will impact snow cover and mean annual temper-atures, and this is going to significantly increase the over-winternitrogen mineralization (8), yet we know very little about field-scale ammonia oxidation processes in arctic ecosystems. The ox-idation of ammonia to nitrite is the first and rate-limiting step ofnitrification. In soil, ammonia oxidation is regulated by a combi-nation of the ammonia-oxidizing communities (59) and soilphysicochemical properties (7). The purpose of this investigationwas to characterize how the biology of aerobic ammonia oxidation(functional gene abundance and biochemistry) interacts with soilchemistry and pedology of arctic ecosystems to influence field-scale ammonia oxidation processes. Understanding how molecu-lar scales (genes) are linked to field scales will enable researchers todevelop a holistic understanding of how climate change will driveevolutionary and ecological processes in arctic ecosystems.

One approach to linking molecular to field-scale processes isthrough the analysis of spatial dependency of these processes. Spa-tial dependency arises because soil properties are inherently het-erogeneous and this spatial heterogeneity is predominantly “non-random” (25). In other words, as distance between two points inspace declines, samples become more similar. This similarity is

driven because as the intersample distance declines, the variationof soil properties due to differences in topography, climate, soilphysicochemical and biological processes, and vegetation declines(1, 10, 13). Thus, the spatial dependency of a process reflects theunderlying mass and energy flows of an ecosystem at a field scale.As such, a comparison of how molecular parameters for example,gene abundance, are spatially dependent compared to the spatialdependency of larger processes, such as pedological characteris-tics, allows one to infer ecosystem-level linkages between theseparameters. Microbial communities are spatially dependent (19),with previous studies focusing on grassland (45, 53), agricultural(22, 27), forest (55), and arctic (2) soils. In the present study wesought to build on this foundation by linking enzymatic processes(ammonia oxidation) to gene abundance and explore how theselinks are driven by pedological features of arctic ecosystems.

Aerobic ammonia oxidation in soil is governed by chemo-lithoautotrophic and heterotrophic microbial communities. Un-like autotrophic ammonia oxidizers, ammonia oxidation in het-erotrophic bacteria is not related to their cellular growth (15). Theimportance of heterotrophic ammonia oxidation in soil has longbeen recognized (60), but no information is available on this path-way in cryosols. This lack of knowledge regarding the autotrophicand heterotrophic ammonia oxidation processes may be due tothe fact that cryosols are typically nitrogen limited and a consid-

Received 8 July 2011 Accepted 1 November 2011

Published ahead of print 11 November 2011

Address correspondence to S. D. Siciliano, steven.siciliano@usask.ca.

Supplemental material for this article may be found at http://aem.asm.org/.

Copyright © 2012, American Society for Microbiology. All Rights Reserved.

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erable proportion of cryosols are acidic in nature, which reducesammonia bioavailability for ammonia oxidation. The abundanceand functions of ammonia-oxidizing bacteria and archaea in soilare influenced by various soil factors, including moisture, pH,ammonium, organic carbon content, and temperature (18, 38, 40,46, 63) that operate at multiple spatial scales. In the present study,we investigated spatial patterns of aerobic ammonia-oxidizingfunctional groups in three arctic ecosystems to answer the follow-ing questions. (i) What is the relative abundance of aerobicammonia-oxidizing bacteria and archaea in arctic soils? (ii) Whatis the autotrophic and heterotrophic ammonia oxidation poten-tial in various types of cryosols? (iii) Finally, what are the drivingfactors of ammonia oxidation at different spatial scales in arcticsoils?

MATERIALS AND METHODSSite description. The present study was conducted at three high arcticsites: Truelove Lowland, Simpson Lake, and Ross Point (Fig. 1). The True-love Lowland site (75°40=N, 84°35=W) has already been extensively de-scribed (6, 37, 64). The average July soil temperature in the upper 5 cm in2008 was 13°C, with a maximum value of 24°C and a minimum of 6°C(17). This coastal lowland is situated on the northeastern coast of DevonIsland, and it covers an area of 43 km2 of Devon Island’s 55,000-km2 area.The topography of Truelove Lowland is distinguished by a series of raisedbeach crest ridge, lower foresope, and wet sedge meadow with regosolicstatic cryosols, brunisolic eutric turbic cryosols, and gleysolic turbic cryo-sols, respectively (64). The mean annual air temperature is approximately

�16°C, with the highest recorded daily temperature of 21°C in July and�45°C as the lowest monthly temperatures (6, 37). The total annual pre-cipitation is about 185 mm, with 36 mm as rain. Simpson Lake (68°35=N,91°57=W) is located in the middle of the Boothia Peninsula, ca. 80 km westof Kugaaruk and 120 km east of Gjoa Haven. Historical data from Ku-gaaruk suggest that the temperature in winter (December-January) variesbetween �23°C and �37°C and in summer (July-August) varies between4°C and 24°C (17). The total annual precipitation is about 260 mm with110 mm as rain. The upper-slope positions are comprised of static cryo-sols, whereas lower-slope positions are turbic cryosols. Ross Point(68°31=N, 111°10=W) is situated in the south port of Victoria Island, thesecond largest island in the Canadian Arctic archipelago. The experimen-tal site is dominated by lichen and dry heath vegetation. Ross Point(68°31=N, 111°10=W) is situated in the southern part of Victoria Island.This site is about 150 km west of the town of Cambridge Bay. Historicalweather data from the last 30 years in Cambridge Bay suggest the temper-ature in summer (July-August) ranges between 4°C and 23°C and in win-ter (December-January) between �25°C and �36°C (17). The mean an-nual precipitation is about 138 mm, with 69 mm as rain. The soils at RossPoint are predominantly organic cryosols.

Soil sampling design. Soil samples were collected during third andfourth weeks of July in 2006. Three parallel transects (300 m each; 2-mdistance between each of the transects) were established at each researchsite. Soil samples were collected at 31 points (0, 0.1, 0.2, 0.5, 1, 2, 5, 10, 20,50, 100, 100.1, 100.2, 100.5, 101, 102, 105, 110, 120, 150, 200, 200.1, 200.2,200.5, 201, 202, 205, 210, 220, 250, and 300 m) along each transect. A GPSunit (Trimble GPS Systems, California) was used to identify spacing (�8cm) between samples. Approximately 250 g of soil samples was collected

FIG 1 Geographic location of three experimental sites in circumpolar arctic region: Truelove Lowland (75°40=N, 84°35=W), Simpson Lake (68°35=N, 91°57=W),and Ross Point (68°31=N, 111°10=W). Adapted from the Toolik-Arctic Geobotanical Atlas (www.arcticatlas.org; Alaska Geobotany Center).

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at a 1- to 10-cm depth using a hand trowel and sieved with a 4.75-mmsieve. Between samples, sieves and hand trowels were sterilized with 95%ethanol and dried before use. Since facilities for performing chemical andmolecular analyses were not available on site, the soil samples were frozenat �20°C and shipped to the laboratory at the University of Saskatchewan.

For spatial comparison, we sought to use the same design at threeresearch sites. In our experience, a single long transect in the polar regionsis often compromised because of erratic boulders, frost wedges, meltponds, and unstable slopes. Three transects provide a reasonable approx-imation of a typical strip of land in the arctic regions, whereas a singletransect line often will not. For example, a 300-m-by-300-m grid designwas not possible to establish at Truelove Lowland. Moreover, fine-scalepatterns may not be captured with a grid design due to its even lag distance(minimum of 2 or 4 m). Variable (irregular) sampling design, adjacentsteps separated by a repeated sequence, is a particularly useful design forsubstantiating multi-scale patterns in an ecosystem (20, 21, 42). There-fore, in the present study, we specifically used a variable-lag-distance tran-sect approach to simultaneously capture the fine-scale (0 to 1 m),medium-scale (1 to 10 m), and large-scale (10 to 300 m) spatial patterns ofmicrobial communities in three cryosolic ecosystems.

Soil analyses. Soil gravimetric water content was determined by mea-suring the weight loss of 5-g soil samples after they were dried for 24 h at105°C and are expressed as a percentage (23). Soil pH was measured byusing 5 g of soil in a 1:1 soil-water (deionized) mixture with an AccumetpH meter (Accumet 925; Fischer Scientific, MA). For exchangeable am-monium NH4

�) and nitrate (NO3�) content, soil subsamples were

shaken with 0.5 M K2SO4 (1:10 soil-K2SO4) for 1 h and filtered usingWhatman 90-�m-pore-size filter papers (Maidstone, Kent, England). A3-ml aliquot of extract was analyzed by using a SmartChem200 discretechemistry analyzer (Westco Scientific Instruments, Inc., CT). The totalorganic carbon (TOC) content was determined by using the Leco CR-12carbon analyzer (LECO Corp., St. Joseph, MI). The determined quantityis expressed as a percentage of the soil mass.

Autotrophic ammonia oxidation potential (AOP). Potential ammo-nia oxidation is an estimation of the production of nitrite in soil (66). Inbrief, a test medium was prepared with 4 mM ammonium sulfate, 15 mMsodium chlorate, and 1 mM monopotassium phosphate buffer (pH 7.2).In this test medium, ammonium sulfate is an energy source, sodium chlo-rate inhibits the oxidation of nitrite to nitrate (5, 24), and monopotassiumphosphate buffers the medium. Ammonium sulfate is added as a one-timesupplement to the soil to achieve the maximum ammonia oxidation po-tential of a soil. The concentration of ammonium sulfate was selectedfrom previous studies on polar soils (57, 58), where it was found thataverage ammonia oxidation potential using this method is strongly cor-related (r � 0.66) with 15N ammonia oxidation in polar soils (30). Soil (5g of fresh weight) was added to 20 ml of test solution, the mixture wasshaken (100 rpm) at room temperature (20°C) for 28 h (the time pointwas selected based on a time course assay), and an aliquot of 2 ml wascollected. Immediately after collection, 2 ml of 4 M KCl was added to stopthe ammonia oxidation, and the mixture was centrifuged at 13,000 rpmfor 3 min and filtered through a 0.45-�m-pore-size syringe filter to re-move particulate matter. Then, 3 ml of filtrate was taken for nitriteanalysis according to the Griess-Illosvay technique (24, 66) using a spec-trophotometer (Beckman Du-650; Beckman Coulter, CA). The concen-tration of nitrite was expressed as ng of NO2

�-N g of dry soil�1 h�1.

Typically, potential ammonia oxidation is measured at 20°C (24, 66). Itshould be noted that the soil samples were collected in summer (thefourth week of July), and these research sites regularly experience temper-ature as high as 24°C during midday in summer (17). Soil biological assaysin previous studies conducted on Truelove Lowland soils also used 20°Cas the incubation temperature (6). Thus, the incubation temperature se-lected for the AOP assay in the present study can be representative of themidday temperature during growing season. We selected a single incuba-tion temperature (20°C) for consistent measurement of soil samples col-lected from all three sites.

HAOP assay. A heterotrophic ammonia oxidation potential (HAOP)assay was performed using the same method as for the AOP assay exceptthat 400 �g of nitrapyrin was mixed with 5 g of fresh soil, followed byincubation for 6 h before the test medium was added to the soil. Ni-trapyrin is the longest known and best inhibitor of chemoautotrophicammonia oxidizers (11, 50) and differentiates between heterotrophic andautotrophic ammonia oxidation (15). The concentration of nitrapyrinwas selected from a previous study (33), which found that 80 mg g ofsoil�1 is the most effective concentration that completely inhibitedautotrophic ammonia oxidation. However, the effect nitrapyrin onammonia-oxidizing archaeal population is not yet well known; thus, het-erotrophic ammonia oxidation measured in the present study actuallypertains to nitrapyrin-inhibited ammonia oxidation potential.

DNA extraction and quantification of ammonia-oxidizer abun-dance. DNA extraction from soils was done according to a method de-scribed earlier (26) with the modification that the DNA samples wereprecipitated in polyethylene glycol overnight. The concentration of puri-fied DNA was determined by using a spectrophotometer (Ultrospec 2000UV/visible spectrophotometer; Pharmacia Biotech, Cambridge, UnitedKingdom). The numbers of bacterial amoA and archaeal amoA genespresent in soil DNA extracts were determined by conducting quantitativereal-time PCR (qPCR) using a QuantiTect SYBR Green PCR Master Mixreal-time PCR kit and an ABI 7500 real-time PCR machine (Applied Bio-systems). The primer sets amoA-1F/amoA-2R (54) and Arch-amoAF/Arch-amoAR (49) were used for the bacterial amoA and archaeal amoAassays, respectively. Each 20-�l reaction contained 10 �l of master mix, 10pmol of the appropriate forward and reverse primers, 6 �l of sterilizedMilli-Q water, and 2 �l of template DNA (1:10 diluted). The thermalcycling program for the genes was as follows: 97°C for 15 min, followed by45 cycles of 94°C for 20 s, 54°C for 40 s, and 72°C for 40 s, and then 77°Cfor 45 s, followed by a melting-curve analysis from 50 to 95°C. Standardswere prepared by amplifying community DNA and purifying the ampli-fied products for use in a qPCR assay. We also prepared qPCR standardsusing genomic DNA extracts of Nitrosomonas europaea to compare tothese community DNA standards (see the protocol and Fig. S1 in thesupplemental material for more details). The number of gene copies pres-ent in the product was estimated by determining the concentration ofDNA in the product (41). Only standard curves linear over 5 orders ofmagnitude were selected, and standards were run on each individualqPCR plate. For both genes, the efficiency of the reaction was between 86and 100% (based on the slope of the standard curves). The r2 value for thestandard curves was 0.99 for all assays except bacterial amoA at TrueloveLowland and Simpson Lake, which was 0.98. The specificity of the ampli-fied products was assessed by melting-curve analysis. Amplification inhi-bition effects were assessed by assessing gene abundance on three differentdilutions of representative samples and selecting the dilution that mini-mizes the inhibition (16).

Geostatistical analyses. The recorded data were tested for homogene-ity of variances (Bartlett’s and Levene’s tests) and normality (Anderson-Darling) using Minitab (version 14) software. We estimated the back-ground variability associated with molecular methods applied to soilsamples. To determine the DNA extraction variability, DNA was extractedusing 0.5 g of soil from 10 replicates of one soil sample, which comprises250 g of soil, and assessed the samples for bacterial amoA and archaealamoA abundance. Variability associated with soil subsampling was calcu-lated as the variance of 10 independent trials of the same soil sample. TheqPCR variability was estimated by averaging the variance of between 5 and10 qPCR estimations of six different samples for bacterial amoA and sevensamples for archaeal amoA. Variances were divided by 2 to compare withexperimental semivariance of spatial analyses.

The spatial heterogeneity and spatial relationships among the vari-ables were estimated using geostatistical analyses. In geostatistics, the de-gree of spatial continuity of a variable is assessed by analyzing the dissim-ilarity between two observations as a function of the separation distanceor lag distance. One way to assess this dissimilarity is through computing

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semivariance, �(h), which is the half of the average squared differencebetween the components of a data pair:

�(h) �1

2N(h) �k�1

N(h)

[z(xk) � z(xk � h)]2

Here, z(xk) is the property, z(xk � h) is the value at h lag distance, and N(h)is the number of data pairs for a given distance (25). A semivariogram is aplot of the semivariance, �(h), as a function of h or lag distance. Threeimportant attributes of a semivariogram are nugget variance, sill, andrange. The nugget variance is the stochastic variation, which is contrib-uted by measurement or experimental error. Sill is the maximum variabil-ity attained by the variable, and range is the lag distance at which thesemivariance value becomes highest. The range of a semivariogram indi-cates the zone of spatial dependency. In other words, samples spacedcloser than the range are spatially dependent, whereas samples separatedby a distance greater than the range are not spatially dependent. Thespatial dependence of the soil properties and gene abundance was calcu-lated by semivariogram analysis. Spatial dependence (SPD) � C/(C �C0), where C is the structural variance, C0 is the nugget, and C � C0 is thesill. Values of SPD vary from 0 (no spatial dependence) to 1 (strong spatialdependence). The spatial association between two variables can be deter-mined by calculating the cross-semivariance, �yz(h):

�yz(h) �1

2N(h) �k�1

N(h)

[y(xk) � y(xk � h)] . [z(xk) � z(xk � h)]

where y and z are two variables, z(xk � h) is the value at h lag distance, andN(h) is the number of data pairs for a given distance. A plot of cross-semivariance, �yz(h), as a function of h or lag is called the cross-semivariogram. All semivariograms and cross-semivariograms were cal-culated with a minimum of 30 sample pairs per lag class (35). Various

models such as Gaussian, spherical, exponential were fitted to the semi-variograms and cross-semivariograms using a least-squares method.Three specific scales were selected for estimating scale dependent associ-ations among the variables: fine (0 to 1 m), medium (1 to 10 m), and large(10 to 100 m). All geostatistical analyses were performed using GS� ver-sion 9 (Gamma Design Software, Plainwell, MI).

RESULTSFunctional gene abundance, ammonia oxidation potential, andsoil attributes. We found high abundance of bacterial amoA (105

to 107 copies g of dry soil�1) and archaeal amoA (106 to 108 copiesg of dry soil�1) genes in arctic soils (Fig. 2). The three cryosolicecosystems selected in the present study showed considerably highammonia oxidation potential. The contributions of heterotrophsat Truelove and Simpson Lake were 35 and 29%, respectively, ofthe total ammonia oxidation potential, despite the moderate acid-ity of Simpson Lake soils (see Table S1 in the supplemental mate-rial). At Ross Point, the heterotrophs contribute up to 47%, whichmay be linked to the higher TOC and moisture content comparedto the other two sites.

Analysis of spatial dependency. Spatial variability of the bac-terial amoA gene (sill variance � 1.02) is substantially higher thanthe variance associated with DNA extraction (0.12) and quantify-ing genes by qPCR (0.17) (Fig. 3). The bacterial amoA gene atTruelove is spatially autocorrelated with the spherical model pro-viding a fit of r2 � 0.31, P � 0.01 and a spatial range of 2.6 m.Spatial dependence explains the majority of experimental vari-ance associated with ammonia oxidizer abundance and ammoniaoxidation potential (Fig. 4). However, the spatial dependency ofarchaeal amoA at Truelove Lowland, AOP at Simpson Lake, andHAOP at Ross Point could not be captured with the transect de-sign, which suggests that either (i) there is no significant spatialdependency or (ii) the dependency operates at a �0.2-m distance(double our smallest lag distance). Bacterial amoA, archaealamoA, and AOP differ from one another in their spatial structures.

FIG 2 Log gene copy numbers of ammonia-oxidizing functional groups (ar-chaeal amoA and bacterial amoA) (A) and overall ammonia oxidation poten-tial (AOP) and heterotrophic ammonia oxidation potential (HAOP) (B) atthree arctic sites: Truelove Lowland, Simpson Lake, and Ross Point.

FIG 3 Semivariogram of bacterial amoA showing spatial variability at True-love Lowland compared to experimental error associated with extracting andquantifying genes in soil. The qPCR variability (semivariance � 0.17; n � sixindependent DNA extracts, with 10 qPCR replicates each) and DNA extractionvariability (semivariance � 0.12; n � 10 independent extractions [0.5 g, freshweight] of the same 300-g soil sample, which were then analyzed by qPCR intriplicate) are indicated as a long dash and a dotted line, respectively.

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Bacterial amoA abundance is spatially structured at all three siteswith a consistent spatial range (2.2 to 2.6 m). In contrast, archaealamoA abundance is not consistently spatially dependent at all siteswith a range between 2.2 and 4.4 m. In spite of these differences,bacterial amoA and archaeal amoA are spatially correlated (P �0.05) at all three sites, with cross-semivariance ranges between 3and 4.5 m and SPD values between 0.38 and 0.85 (see Fig. S2 in thesupplemental material). AOP has the largest spatial range (22 to 41m) and considerably high spatial dependence. The spatial range ofthe relationships between AOP and soil properties varies greatlybetween sites. For example, the cross-semivariance between AOPand soil properties (P � 0.05) has a range of �20 m at Ross Pointbut only 0.3 m at Simpson Lake (see Fig. S3 in the supplementalmaterial). There are weak correlations between the AOP andHAOP potential at Truelove (Spearman Rank [�] � 0.39, P �0.01), none at Simpson Lake (� � �0.15, P � 0.16), and weaklinks again at Ross Point (� � �0.28, P � 0.01). This suggests thatheterotrophic contribution to total ammonia oxidation potential,estimated as HAOP/AOP, is variable across the site. The HAOP is

spatially dependent at Truelove Lowland, and HAOP/AOP valuesare spatially dependent at two of the three sites, with a range be-tween 8.3 and 14 m and an SPD between 0.55 and 0.65 Lake (seeFig. S4 in the supplemental material).

Spatial relationships between AOP and ammonia oxidizerabundance mostly operate at medium scale (Table 1). The testedsoil attributes that regulate the AOP at fine scale, �1 m, are mois-ture content and TOC. Soil moisture is strongly correlated to AOPat all scales for all three sites; similarly, the TOC content is alsosignificantly correlated in most cases. Other soil attributes such aspH, ammonia, and nitrate content interact with AOP at a mediumor large scale.

DISCUSSION

The bacterial and archaeal amoA gene abundance is similar towhat previously seen in arctic (105 to 107 and 106 to 108 copies g ofdry soil�1, respectively), agricultural (106 and 107 copies g of drysoil�1, respectively), and pristine (107 and 108 copies g of drysoil�1, respectively) soils (31, 34, 36, 63, 64). The high abundance

FIG 4 Semivariograms showing differential spatial structure of bacterial amoA abundance (AOB), archaeal amoA abundance (AOA), and potential ammoniaoxidation (AOP) at three arctic sites: Truelove Lowland (TR), Simpson Lake (SL), and Ross Point (RP). Spatial dependency (SPD) was considered from fine scale(10 cm) to large scale (300 m). The values of SPD vary from 0 (no spatial dependence) to 1 (strong spatial dependence). Range indicates the zone of spatialdependency. Different models (Gaussian, spherical, and exponential) were fitted (solid line) to each semivariogram. Semivariograms are shown up to the specificlag distance for clarity of the spatial patterns near the origin.

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of bacterial and archaeal ammonia-oxidizing archaea and bacteriamay indicate the existence of microhabitat partitioning and dis-tinct ecological niches in arctic soils (61). The cospatial depen-dency between bacterial and archaeal amoA suggest that the abun-dance of ammonia oxidizers is being modulated by similar soilparameters that are occurring at the �5-m scale. However, theqPCR primers used in the present study to assess the ammoniaoxidizer abundance have reduced or lower coverage, and it is pos-sible that the primers may have missed a portion of the AOA andAOB abundance. For instance, the AOA primers used here do notcover several archaeal genera, such as Nitrosocaldus yellowstonii,Nitrosopumilus maritimus, and Crenarcheum symbiosum, andsimilarly the AOB primers also do not cover all of the bacterialammonia oxidizers (62, 65). Therefore, these primers may haveunderestimated the ammonia-oxidizing populations, and the ac-tual abundance in these cryosolic ecosystems may even be largerthan what is reported here.

The link between DNA contents and activity in the field is notconclusive and, thus, increased gene copies do not conclusivelymean that activity will be increased. In addition, the archaealammonia monooxygenase belongs to the family of copper-containing membrane-bound monooxygenases that have a widesubstrate range, including methane, ammonia, and short-chainedalkanes. Further, only 5 of 10,000 deposited archaeal amoA se-quences are actually linked to established AOA (29, 51, 56, 61).Thus, the genes assessed here may also be coding for enzymes notdirectly linked to ammonia oxidation. Another limitation ofDNA-based qPCR results is that in situ extracellular DNA mayinterfere with the interpretation of our results. Although no re-ports are available from Arctic soil environments, microbial ex-tracellular DNA molecules may persist anytime between 30 min to70 days in soil (47). Thus, it is also possible that some of theammonia oxidizer DNA molecules quantified in the present studydo not actually belong to active functional ammonia oxidizer pop-ulation and are not essentially contributing to ammonia oxida-tion. Moreover, it has been found that the length of the bead-beating time involved in DNA extraction may also influenceammonia oxidizer abundance since the AOB copy number mayincrease and AOA copy number decrease with the time of beadbeating (38). Therefore, the results reported here only intend topresent a comparative account of the relative changes in the twogroups of ammonia oxidizer populations. Nonetheless, the AOPat Truelove Lowland (68 ng of NO2

�-N g of dry soil�1 h�1) isthree times higher than that Simpson Lake (21 ng of NO2

�-N g ofdry soil�1 h�1) and about half of Ross Point (178 ng of NO2

�-N g

of dry soil�1 h�1). It should be noted that Truelove Lowland is apolar oasis, whereas Simpson Lake is a typical arctic ecosystem,which does not benefit from the increased moisture and temper-ature typical of a polar oasis such as Truelove Lowland. On theother hand, the organic cryosols of Ross Point have higher mois-ture and ammonia content and optimum pH, which is conducivefor ammonia oxidation. The overall AOP at Ross Point is in asimilar range as for the agricultural soils (0.1 to 1.5 �g of NO2

�-Ng of dry soil�1 h�1) (31, 63).

Heterotrophic ammonia oxidation comprises a considerableproportion of the overall ammonia oxidation potential. In arcticsoils with moderate moisture and ammonium content (TrueloveLowland and Simpson Lake) heterotrophs contribute as much asone-third of total ammonia oxidation. In a soil with high mois-ture, ammonium, and organic matter content (Ross Point), het-erotrophs contribute up to 47% of the overall soil ammonia oxi-dation potential. The contribution of heterotrophs to soilammonia oxidation potential is consistent with a previous report(43) that heterotrophic ammonia oxidation N-cycling processesmay dominate in situ N transformations in some soils with highorganic matter. Nonetheless, the high contribution of hetero-trophs at Ross Point may also have resulted from reduced effec-tiveness of nitrapyrin in organic soils (11, 44). Autotrophic am-monia oxidation may not have been inhibited completely due tothe sorption of nitrapyrin in organic soils. Moreover, the efficacyof nitrapyrin to inhibit ammonia-oxidizing archaeal populationhas not yet been tested. Aerobic ammonia oxidation by hetero-trophs is currently not understood at the molecular level, and theammonia-oxidizing gene sequence in heterotrophs is not wellcharacterized. The present study could not link heterotrophic am-monia oxidation to functional gene abundance. The discoveryand elucidation of heterotrophic ammonia-oxidizing gene targetsmay identify a fine-scale process linking observed potential in soilsto gene abundance and expression.

Considerable spatial dependency of microbial abundance andcommunity structure have been demonstrated in grassland (45,52, 53), agricultural (22, 27, 28), forest (55), contaminated (3),and arctic soils (2). We show here that in spite of cryopedogenicprocesses, the ammonia-oxidizing archaeal and bacterial popula-tions and ammonia oxidation processes are spatially well struc-tured in different types of cryosols. Spatial dependency and rangeare influenced by soil sampling design (20). The spatial range weobserved for microbial communities in this study resembles thatseen by others in agricultural soils (22). The high spatial depen-dency suggests that we were able to capture the majority of the

TABLE 1 Spatial scale-dependent correlations between autotrophic ammonia oxidation potential, functional groups, and environmental variables

Comparison

Correlation (P)

Truelove Lowland Simpson Lake Ross Point

Fine Medium Large Fine Medium Large Fine Medium Large

AOP vs bacterial amoA NS NS NS 0.29* NS NS NS 0.30* NSAOP vs archaeal amoA NS 0.33* 0.35* NS 0.42** NS NS 0.37* NSAOP vs moisture 0.27* 0.35* 0.27* 0.71** 0.64** 0.60** 0.45** 0.25* 0.35*AOP vs pH NS NS NS NS NS –0.36* NS –0.36* –0.32*AOP vs NH4

� NS 0.31* 0.26* NS NS 0.29* NS NS 0.36*AOP vs NO3

� NS NS 0.25* NS 0.62** NS NS NS 0.25*AOP vs TOC NS 0.37* 0.30* 0.48** 0.42** NS 0.38** 0.27* 0.43**aAOP, ammonia oxidation potential. Scale: fine, 0 to 1 m; medium, 1 to 10 m; large, 10 to 100 m. NS, not significant; �, significant at P � 0.05; ��, significant at P � 0.01.

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spatial variability in these locations. In agriculture soils, previousresearch (22) showed nested scaling patterns of microbial spatialheterogeneity, although it was also found (48) that the determi-nants of bacterial distribution operate only at microscale in topsoiland nested spatial scales in subsoil. Other ecosystems are alsoknown to operate at multiple scales (14), and this spatial depen-dency will bias random sampling schemes so that the very rare andvery common members of the microbial community are sampled(27). Our work found that the spatial dependencies of arctic soilsis similar to other systems and supports the conclusion drawn byChu et al. (12) that broad genus-level microbial diversity does notdiffer across ecotypes since it appears that similar soil factors driveecosystems across ecotypes. Based on our results, investigatorsusing a statistical design that assumes sample independence, e.g.,an analysis of variance-based design, should use a spatially explicitsampling regime to estimate microbial abundance and functionsin arctic soils with a minimum distance for gene abundance stud-ies of 5 m and for biochemical processes an intersample distanceof 40 m.

Like previous researchers (4), we observed relatively large-scalespatial dependencies of biological properties across a study area inwhich soil type remains largely similar. Thus, while it is oftenthought that the scale of biological processes that lead to spatialdependency occurs at medium scales, i.e., �10 m, our study and aprevious study (4) suggest that large-scale biological processes (10to 100 m) can also shape spatial structure. The relationshipsamong ammonia oxidation potential, soil properties, andammonia-oxidizing population are nested within one another. Atthe large scale (10 to 100 m) all of the studied soil properties arecorrelated to AOP. The high correlations between soil moisturecontent and AOP at all scales suggest that moisture, along with soilorganic carbon, is a key regulator of the spatial patterns of ammo-nia oxidation in arctic soils. In addition to moisture and soil or-ganic carbon, the population size of ammonia-oxidizing bacteriaand archaea is linked to AOP at the fine and medium scales (0.1 to10 m). It should be noted that sodium chlorate may not be aneffective inhibitor of nitrite oxidation by Nitrospira, which mayalso influence the AOP assay (32). Nonetheless, it can be surmisedthat soil attributes rather than functional genes are the principaldeterminants of potential ammonia oxidation in arctic soils. Thisis the first study assessing autotrophic and heterotrophic ammo-nia oxidation potential and their driving factors in arctic soils; it isnot clear from our study how climate change will cascade throughthe soil factors to the functional genes and ammonia oxidation inarctic soils.

ACKNOWLEDGMENTS

This study was supported by Climate Change Impacts on Canadian ArcticTundra (CiCAT) and International Polar Year (IPY).

Logistical support was provided by the Polar Continental Shelf Pro-ject, with field assistance provided by A. Schafer and S. Ferguson. Wethank the anonymous reviewers for insightful comments and constructivesuggestions.

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